1 University of Washington Faculty Council on Research January 9 th , 2019 9:00 a.m. – 10:30 a.m. Gerberding 142 Meeting Synopsis 1. Call to order 2. Review of the minutes from November 14, 2018 3. Presentation Applied Physics Lab – UW: Lisa Zurk, PhD, APL-UW Executive Director and Robert T Miyamoto, Associate Director APL-UW 4. Discussion on Class C Resolution for Lab Safety (Approved draft attached) 5. FCR Review of amended EO 53 Animal Use (E053: 4 documents) 6. Team science and the demographics of the scientific workforce (Milojevic S, et al. PNAS 2018; 115) 7. Discussion and vote on contract waiver request: 1) APL-UW Waiver request from Peter Dahl 8. Good of the order 9. Adjourn _________________________________________________________________________________________ 1. Call to order The meeting was called to order at 9:00 a.m. 2. Review of the minutes from November 14, 2018 The minutes from November 14, 2018 were approved as written. 3. Presentation Applied Physics Lab – UW: Lisa Zurk, PhD, APL-UW Executive Director and Robert T Miyamoto, Associate Director APL-UW Robert Miyamoto, Associate Director of the UW Applied Physics Lab (APL), provided an overview of the UW APL using a PowerPoint presentation (Exhibit 1). 4. Discussion on Class C Resolution for Lab Safety (Approved draft attached) Frevert, the chair, updated the council on the status of the Class C resolution for Lab Safety. The Senate Executive Committee (SEC) made an amendment to the language (Exhibit 2). Members discussed whether the amendment takes away authority or if the University has authority to enforce EH&S lab safety standards/procedures. The chair noted that the amendment came directly from the President and was agreed upon by the SEC. The Provost has also called for a task force to further establish policy to reinforce this resolution. A member commented that the task force should address fieldwork safety. The chair responded that after speaking with EH&S that fieldwork was important, but added complexity to the issue. EH&S recommended addressing fieldwork safety after lab safety policy and procedures were established. Other members agreed that fieldwork safety is an issue that the council should take up. The chair asked for volunteers to sit on the task force. Mike Rosenfeld volunteered to represent the council. 5. FCR Review of amended EO 53 Animal Use (E053: 4 documents)
Transcript
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University of Washington Faculty Council on Research
January 9th, 2019 9:00 a.m. – 10:30 a.m.
Gerberding 142 Meeting Synopsis 1. Call to order 2. Review of the minutes from November 14, 2018 3. Presentation Applied Physics Lab – UW: Lisa Zurk, PhD, APL-UW Executive Director and Robert T
Miyamoto, Associate Director APL-UW 4. Discussion on Class C Resolution for Lab Safety (Approved draft attached) 5. FCR Review of amended EO 53 Animal Use (E053: 4 documents) 6. Team science and the demographics of the scientific workforce (Milojevic S, et al. PNAS 2018; 115) 7. Discussion and vote on contract waiver request: 1) APL-UW Waiver request from Peter Dahl 8. Good of the order 9. Adjourn _________________________________________________________________________________________ 1. Call to order The meeting was called to order at 9:00 a.m. 2. Review of the minutes from November 14, 2018 The minutes from November 14, 2018 were approved as written. 3. Presentation Applied Physics Lab – UW: Lisa Zurk, PhD, APL-UW Executive Director and Robert T
Miyamoto, Associate Director APL-UW Robert Miyamoto, Associate Director of the UW Applied Physics Lab (APL), provided an overview of the UW APL using a PowerPoint presentation (Exhibit 1). 4. Discussion on Class C Resolution for Lab Safety (Approved draft attached) Frevert, the chair, updated the council on the status of the Class C resolution for Lab Safety. The Senate Executive Committee (SEC) made an amendment to the language (Exhibit 2). Members discussed whether the amendment takes away authority or if the University has authority to enforce EH&S lab safety standards/procedures. The chair noted that the amendment came directly from the President and was agreed upon by the SEC. The Provost has also called for a task force to further establish policy to reinforce this resolution. A member commented that the task force should address fieldwork safety. The chair responded that after speaking with EH&S that fieldwork was important, but added complexity to the issue. EH&S recommended addressing fieldwork safety after lab safety policy and procedures were established. Other members agreed that fieldwork safety is an issue that the council should take up. The chair asked for volunteers to sit on the task force. Mike Rosenfeld volunteered to represent the council. 5. FCR Review of amended EO 53 Animal Use (E053: 4 documents)
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The chair shared that the Faculty Senate Chair asked FCR to review proposed amendments to Executive Order (EO) 53 which dictates policy on experimental animal use at the University (Exhibits 3, 4, 5 & 6). The chair asked for feedback from the council. A member asked if the University had considered alternatives to experimental use on animals. The chair responded that the University has guidelines to reduce, replace and refine so that animal use is limited. A member asked about oversight of these sites. The chair responded that the veterinarians are mostly professional staff. The council discussed the role and representation of the Institutional Animal Care and Use Committee (IACUC). The chair shared that a faculty member (not on the council) expressed a concern that IACUC did not consist of representatives with adequate ethics training. A council member agreed that the description of IACUC under the EO is vague. A member provided additional context behind the update. The intention behind this amendment (and amendments for other EOs) is to separate the APS from the policy. This member argued that the language could be more detailed or stronger, but should leave out very specific details so that the EO does not have to be regularly updated. Members discussed that the authority and membership of the IACUC should be clarified. The chair will send the recommendation to the Faculty Senate Chair. 6. Team science and the demographics of the scientific workforce (Milojevic S, et al. PNAS 2018; 115) The chair shared a publication from PNAS (Proceedings of the National Academy of Sciences) which discusses changing demographics of scientific careers (Exhibit 7). The chair related this to the shared resources task force and changing dynamics at the University. There are more Ph.D. scientist who oversee large operations but their funding is soft money. These scientist are likely to have a shorter career at universities under the current (traditional) funding models. Thus, institutions lose out on retaining positions, experience and knowledge. Members discussed whether the University could make changes to avoid a future experience and knowledge (research) deficit. The chair suggested that the council could approach the Washington state legislature or explore more public-private partnerships. A member noted that the concept behind the master plan for the U-District is to increase public-private partnerships at the University. 7. Discussion and vote on contract waiver request: 1) APL-UW Waiver request from Peter Dahl Due to time constraints he council will vote on the contract via electronic vote. 8. Good of the order A member noted that the undergraduate research symposium will take place February 12, 2019. The next FCR meeting, February 13, 2019 is canceled. 9. Adjourn The meeting was adjourned at 10:30 a.m. _____________________________________________________________________________________ Minutes by Lauren Hatchett, [email protected], council analyst
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Present: Faculty: Chuck Frevert (chair), Benjamin Marwick, Michael Rosenfeld, Francis Kim, Sara Kover Ex-officio reps: Ann Glusker, Larry Pierce, Stewart Tolnay President’s designee: Mary Lidstrom Guests: Susan Camber, Jennifer Harris, Robert Miyamoto
Absent: Faculty: Donald Chi, Paul Fishman, Nicole Gibran, Mike Averkiou
Ex-officio reps: JoAnn Taricani
Exhibits Exhibit 1 – FCR_2019_Zurk OverviewSmall.pptx Exhibit 2 – Slide-Discussion on Class C Resolution.pptx Exhibit 3 – EO 53 Amendments Transmittal Letter to Faculty Senate Draft.pdf Exhibit 4 – EO53 Animal Use with client changes - 10-15-2018_stakeholder changes.docx Exhibit 5 – E053 Current-Executive Order Exhibit 6 – E053 Current APS 12.4 Animal Use.pdf Exhibit 7 – Milojevic_2018-Changing demographics in Science.pdf
FCR- 1 January 9th, 2019miyamoto
Lisa ZurkExecutive Director
Bob Miyamoto Associate Executive Director
Applied Physics Laboratory
University of Washington
APL-UW
Presentation to: Faculty Council on Research
Exhibit 1
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Applied Physics Laboratory
University of Washington
Applied Research LaboratoriesUniversity of Texas
Applied Research LaboratoryPennsylvania State University
Applied Physics LaboratoryJohns Hopkins University
Applied Research Laboratory
University of Hawaii(new)
• DoD/Navy-relevant expertise • Rapid response to DoD/Navy needs• Integrated R&D (from basic to applied, across disciplines)
• Student and faculty training in DoD/Navy areas• Technical agent for DoD/Navy
University Affiliated Research Center (UARC)
APL is one of 5 Navy UARCs- Only UARC on west coast
Exhibit 1
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APL: Core Identity University Affiliated Research Center
• Fufiling our mission of providing Navy with cutting edge technology
– Close collaboration with a top-tier university (UW)– Ongoing interaction with industry partners (large industries
and emerging companies)– Interaction with other government partners (NSF, NASA,
NOAA) to bring burgeoning capability to the Navy– Close partnership with Navy brethren and deep
understanding of their unique needs
• Unique and vital capability for the Navy /DoD– Future possible expansions – new building, partnering with
DOE, harvest rapidly evolving technology from industry, etc.
Agile, capable, knowledgeable
Exhibit 1
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R&D Funding and Staff Demographics
FY17 Awards by Sponsor
Office of Naval Research22%
All Other
8%
NSF25%
OtherNAVY16%
NIH5% NOAA
7%
DOD[non-Navy]6%
‘All Other’ includes NIH, DOE, EPA, …‘DOD’ includes DARPA, DTRA, Army, …
Current APL Staff 247Scientists & Engineers 163
(101 PhDs; 28 Women)
Technical Support 27
Admin Support 57
Graduate Students 34
NASA11%
Total: $63.4M (FY18 ~$79M)
Exhibit 1
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Environmental & Information Systems • impact of environment on navy• sonar & signal processing • information & control systems
Field Programs (FY17)world class; covering the globe and varying in scope
Acoustic Reverberation Measurement System South Korea Polynyas, Ice Production, a& Export in the Ross Seas AntarcticaAcross the Channel: Investigating Diurnal Differences Santa Barbara Channel POSYDON North Atlantic OceanApplied Glider Cruises Pacific and Atlantic Oceans Puget Sound Turbulence Tacoma Narrows Puget SoundAutomated Fish Measurement System Bering Sea Quinault River Mouth Washington coastBering Strait - Pacific Gateway to the Arctic Nome to Nome Rapid Assessment Protocol for Inherent optical
properties and Density: Baja Expedition Cabo San Lucas to San DiegoBering Strait Observatory Bering Strait/Chukchi SeaCABAGE Beaufort Sea Robotic Networks for Exploration Under Ice Shelves Antarctica
CARTHE II, Gulf of Mexico Research Initiative -Splash Cruise Gulf of Mexico
ClutterEx Acoustic Target Experiment Gulf of Mexico S Ocean Platform - Wave Glider Experiment Cruise Southern OceanCollaborative Polar Bear Studies Russia Seabed Acoustics Experiment New England ESP Recovery, NANOOS Cruise Washington Coast Seasonal Ice Zone Reconnaissance Surveys (SIZRS) Alaska and Arctic OceanExtreme Conditions Newport (Oregon) Seaweed Project cruises Puget SoundFACT Project - EM-APEX float deployments South China Sea Sediment Acoustic Measurement System Northeast AtlanticFieldwork on Harbor Seals Alaska Shallow Water Reverberation Experiment Geoje Island, South KoreaFloat Testing Puget Sound South China Sea EM-APEX Floats South China SeaGSSM Pressure Instrumentation Monterey Bay, CA Southern Ocean Wave Glider Palmer Station AntarcticaGulkana Glacier ice seismology test Alaska SPURS-2 Eastern tropical Pacific OceanIn Situ Vector Array System South Korea SPURS-2 Lady Amber cruises Eastern Equatorial PacificIntensity Vector Acoustics Experiment Geoje Island, South Korea SPURS-2 Lagrangian Float deployment Eastern Equatorial Pacific
SPURS-2 Seaglider deployments Eastern Equatorial PacificStorm-Driven Near-Inertial Waves and Mixing Western North Pacific
JPL Davis Strait / Mooring Recoveries Greenland Submesoscale Mixed-Layer Dynamics: Isolating the Sub- and Super-Inertial (a.k.a. SMILE Cruise) Pacific Ocean (between Hawaii and Oregon)
Langmuir Circulation DRI Southern California BightLangmuir DRI Cruise Pacific Ocean off San Diego, CA Submesoscale Rapid Salinity and Optics surveys Washington and Oregon coastminiWEC testing Lake Washington Taiwan Eddies Cruise TaiwanNANOOS project Washington Coast Target Signature Near Clutter Gulf of Mexico, Panama City, FLNASCar Glider Deployments Sri Lanka Tests of Vorticity Profiler Lake Washington & Puget SoundNASCar Glider Deployments Arabian Sea, Indian Ocean The Arctic Integrated Ecosystem Research Program Northern Bering Sea/Southern Chukchi SeaNorth Atlantic Aerosol and Marine Ecosystem Study North Atlantic Upper Layer Temperature of the Polar Oceans Survey Alaska and Arctic OceanNorwegian Polar Institute Fram Strait Cruise Tromso, Norway, Fram Strait USRS Experiment Long Island SoundONR Inner Shelf DRI Central Coast of California Washington Ocean Acidification Cruises Puget Sound and WA CoastORCA Shelfish Growth Project Puget Sound WBPR Cruise Oregon CoastPassive Acoustic Monitoring of Marine Mammals Beaufort Sea West Antarctic Circumpolar Deep Water Pathways -
EM-APEX deployments and recoveries Amundsen Sea, AntarcticaPolar Bear Population Assessment Greenland
Exhibit 1
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WOTs are more meaningful APL Faculty Appointments- increase APL’s role in teaching & education- build cooperative research between APL & UW Depts- come with 3+ months of annual support (1.5 mo provided by APL)- provide a new tool for retention & recruitment
UW INTEGRATION: WOTs and Collabsadded 14 more WoT appointments across four UW Colleges; expanded research collaborations with UW units
3 FY09 WOT Appointments: Payman Arabshahi – Electrical EngMike Bailey – Mechanical Eng;UrologyJim Thomson – Civil & Environ Eng
4 FY10 WOT Appointments – in School of Oceanography:Matthew Alford, Kathie Kelly, Craig Lee, and Rebecca Woodgate
2 FY11 WOT Appointments: Andy Jessup – Civil & Environ EngKristin Laidre – Aquatic/Fishery Sciences
2 FY12+ WOT Appointments: Franco Curra – BioengineeringAndy Stewart – Mechanical Eng
Research collaborations across 30+ UW units- notable collaborations include OOI, uWAMIT, FOI, NASA flume, ocean acid., …
Exhibit 1
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• 5-yr construction phase successful• Operations & Maintenance Phase started in 2015
– intended observatory lifespan of 20+ years
APL Research Examples Cabled Observatory
2014 DEPLOYMENT:90 ROV ROPOS dives30 km of extension cable17 junction boxes140 instruments/30 types3 Shallow Profiler moorings1 Deep Profiler mooring1 Surface Piercing Profiler2 benthic expt platforms
Regional Scale Nodes (RSN) with UW Oceanography
Exhibit 1
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Marine Hydrokinetic EnergyConduct R&D for generation devices, resource characterization, and envt’l monitoring instrumentation• advance MHK energy technologies (wave, tidal, and current
systems) for use at naval facilities • provide low-cost tools to quantify marine renewable energy
resources• develop rapidly-deployable energy harvesting systems for tactical
application• SECNAV goal of 50% renewable energy by 2020
APL Research Examples
MHK Test Bed: test & evaluation in Puget Sound
WEBS: Forward-deployed wave energy converter to power tactical undersea network architecture (TUNA) & enable persistent surveillance.
Submarine ICEX’sProvide logistical & technical support for Navy submarine under-ice exercises, including establishment of ice camp, diving services, and customized (digital) underwater tracking range• several successful ICEX’s with testing of weapons
and tactical operations
• camp populations of 50+ and numerous VIPs• additional support of scientific research/visits• ICEX 2018 just completed
Exhibit 1
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Undersea Mobile VehiclesDevelop mobile platforms for undersea exploration, communications networks, and persistent surveillance
- flying wing autonomous underwater glider with payload of advanced sensors
- ocean gliders as communication gateways- next generation gliders- 5-man mini-sub
APL Research Examples
MCM measurements in the GulfAssemble detailed measurements & modeling to provide physical understanding and acoustic fingerprints for mine classification – bi-static and backscattering– proud to fully buried targets– precise geometries (rail sys)
Endon
Broadside
‘Proud Mine’ Data
Exhibit 1
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APL Research Examples
Arctic Observation, Data Collection and Analysis
Comprehensive data to understand the complex & coupled processes that control polar variability and to improve forecasts of weather & ice conditions in Arctic
- network of automatic data buoys to gather oceanographic, meteorological, and ice data
- conducting repeat (every 2-4 week) surveys of atmosphere, ice and ocean from USCG flights
Burst Wave LithotripsyInvestigate new non-invasive ultrasound methods to more effectively fragment kidney stones, replacing more invasive methods and shock wave lithotripsy, which is only successful in 50% of treatments- using focused ultrasound bursts (vice shock
waves) to effectively fragment stones- combining modeling and experiments of stone
fracture and cavitation to guide selection of treatment parameters for optimal breakage
struvite cystine
Exhibit 1
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Collaboratory
“In a typical collaboration ideas are exchanged only as they relate to a specific project. By having a shared collaborative space and by holding open meetings, we are sharing ideas across projects and together brainstorming new opportunities …”
APL-UW hosts a maritime technology accelerator in our waterfront facility. We foster innovation and economic impact, and create dynamic and adaptable teams that respond quickly to rising challenges.
Govenor Inslee and the announcement of the new Washington State Maritime Blue Initiative Jan 8th, 2019
Exhibit 1
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2016 RESEARCH COLLABORATIONS at UWOPD• Joint Proposal on Oxygen Minimum Zone Oceanography • Under Ice Float Oceanography • Influence of wind-driven upwelling and continental slope bathymetry on WA shelf oxygen distributions JISAO • Ocean Modeling Oceanography• SPURS Oceanography • SPURS 2 Oceanography• Stratified rotating flow around complex bathymetry using laboratory and numerical model simulations ME • ORCA Mooring Project Oceanography • Prototype Instrument Testing Oceanography• Puget Sound Hypoxia JISAO• Autonomous Measurements of Plume Eddy Dispersal (AMPED) Oceanography • Transport Pathways through the Caribbean OceanographyEPS Oceanography • Seafloor Pressure Recorder with Wireless Data Offload Oceanography • Offshore Geophysical Network Design for Earthquake and Tsunami Early Warning in the Pacific Northwest Earth & Space Sciences • Geodetic Instrument to Measure Tilt of the Seafloor Oceanography • Regional Scale Nodes/Ocean Observatory Initiative Oceanography EIS• Automated Fish Measurement System EE • MARS PIXL Instrument Earth and Space Sciences• Reactive Landing Chemistry• Energy Usage and Social Identity Feedback in Building Social Networks Civil Engineering• Factional Networks in Fragmented Conflicts Pol. Sci., Computer Science• Forecasting Inter-elite Influence in Fragile States Pol. Sci.• Zero Emission Undersea Signaling EE• Interoperability in Puget Sound Human Center Design and Engineering • Sensor Management EE• Sensitivity analysis of weather prediction models Atmospheric Sciences• Nonstationary Stochastic Processes for Passive Sonar Signal Processing EE • Quantifying the Resilience of Power Systems to Natural Disasters EE • BPA: A Statistical Communication Channel Model for Power System Dynamic Simulation EE • Innova UEV Electric Vehicle Testbed Civil and Environmental Engineering • I/UCRC for Smart Ocean Technology EE • Ocean-TUNE: Community Ocean Testbed for Underwater Network Experiments EE OE• Deep Underwater Wifi Antennas for AUVs EE • Haptically Enabled Corobotics for Remediation of Underwater Military Munitions EE • Wireless Power Transfer for Single Sortie Detect to Engage UUV Mine Countermeasures EE, CS• Haptic Rendering for Raven Surgical Robot EE• Marine Hydrokinetic Energy for Naval Facilities ME, CE
Exhibit 1
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• High Definition Video Camera for RSN, Subsea Telepresence Oceanography• Compressed sensing for Oceanographic Applications and UUV Navigation Applied Math• Smart Ocean Technology Center EE• Novel Sensors, Slam, and Supervised Autonomy for Underwater Inspection Under Extreme Radiation Aeronautics and Astronautics• Marine Mammal PlaybackCIMU• Ultrasound shearing of DNA Allergies and Infectious Diseases • Photoacoustic therapy of blood clots Radiology • Histotripsy treatment of hematomas Radiology • Photoacoustic imaging of blood clots Bioengineering • Label-free cell characterization Bioengineering • Theranostic agents for treating blood clots Chemical Engineering • Drug delivery in the brain using microbubbles Bioengineering • Histotripsy treatment of hematomas Gastroenterology • Contrast Flow Phantom Bioengineering • Ultrasound-based cell sorter Dermatology • Ultrasound contrast flow phantom Radiology • B-Flow imaging Radiology • Kidney Stone imaging ME• Kidney Stone management Radiology • Ultrasound for bones Childrens Hospital – Radiology • Ultrasound Safety for FDA Comparative Medicine• Treatment of Tissue Urology • Tissue and gall stone homogenization Medicine • Ultrasound Imaging Bioengineering • Kidney Injury Medicine - Nephrology • Doppler Ultrasound Simulator Medicine - Cardiology • Doppler Simulator for Vascular Ultrasound Training ME• 3D Ultrasound for Breast Cancer Detection in Low-Resource Countries Medicine - Radiology• MRI-Compatible Fetal Heart Rate Monitor Medicine - Pediatrics• MR-guided drug delivery Medicine - Radiology• HIFU mediated drug delivery Medicine - Gastroenterology• Diabetic tissue properties ME• Ultrasound treatment of Peyronie’s tissue Medicine - Urology• MR evaluation of kidney injury Medicine - Radiology• Evaluation of the Systemic Response to Boiling Histotripsy for Renal Carcinoma Medicine - Urology• Ultrasound treatment of hematomas Medicine - Gastroenterology• Ultrasound treatment of abscesses Medicine – Radiology• Evaluation of liver steatosis Medicine – Pathology• Ultrasound for the mitigation of bone loss Childrens Hospital• Acoustic evaluation of micro and macro steatosis in transplant livers Childrens Hospital – Pathology
2016 RESEARCH COLLABORATIONS at UWExhibit 1
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AIRS• Remote sensing of stream and river surface temperature School of Env. and Forest Sciences• Sources and Impacts of Variability of the Meridional Property Transports in the N. Atlantic Oceanography• Northwest National Marine Renewable Energy Center ME• Turbine Controls ME• Advanced laboratory and field arrays ME• Wave breaking effects on river plumes Civil Env. Eng.• Ocean Surfaces on Snowball Earth Atmospheric Sciences • Development of new radiative transfer code ESS• Ocean Acidification Oceanography• Advanced laboratory and field arrays ME• Wave breaking effects on river plumes Civil Env. Eng.
• Ocean Surfaces on Snowball Earth Atmospheric Sciences • Development of new radiative transfer code ESS• Ocean Acidification OceanographyPSC• Future of Ice Initiative Anthropology, ESS, Oceanography, QRC, PCC, Jackson
Sch.• Glaciology & Remote Sensing Astronomy, ESS, Oceanography, EE• High Latitude Research Oceanography, ESS, Atmospheric Sciences• Sea Ice prediction, PAL Atmospheric Sciences• Ocean Surfaces on Snowball Earth Atmospheric Sciences, ESS• Tidewater Glaciers & Sediment Oceanography, ESS, CEE • Marine Mammals JISAO, Oceanography• International Arctic Institute Jackson School, Aquatic & Fisheries Sciences
OA• Profiling Floats Equipped with Rainfall, Wind Speed, and Biogeochemical Sensors for Use is the Tropical Pac. Obs. Sys. Oceanography• NASCAR (North Arabian Sea Circulation - Autonomous Research Oceanography
2016 RESEARCH COLLABORATIONS at UWExhibit 1
Class C Resolution: Support for the Continuation of the Lab Safety Initiative and for Granting of Legal Enforcement Authority for Environmental Health & Safety
BE IT RESOLVED that the UW Faculty Senate applauds the successful efforts of EH&S in improving laboratory safety at the UW and requests the following:
Approved language:
1. That the Washington State Attorney General’s office determine how EH&S can be granted legal authority to enforce compliance with best laboratory safety practices in all laboratories at the UW.
Amended language:
1. That the provost work with faculty to develop protocols on how EH&S can enforce compliance with best laboratory safety practice in all laboratories at the UW.
Exhibit 2
December 3, 2018 TO: Michael Townsend
Secretary of the Faculty
COPY: George Sandison
Faculty Senate Chair Margaret Shepherd Chief Strategy Officer Executive Office of the President and Provost
SUBJECT: Faculty Senate Review of Executive Order No. 53, “Use of Animals” On behalf of President Cauce, attached please find proposed amendments to Executive Order (EO) No. 53, “Use of Animals” for your review and comment pursuant to Executive Order No. 3, “Executive Order and Administrative Order Procedure.” Background Currently, we have EO 53 and APS 12.4 dictating policy on animal use at the University. Executive Order No. 53, “Use of Experimental Animals”, previously housed in the now defunct University Handbook, consists largely of a paragraph describing the University’s desire to treat animals humanely but doesn’t rise to the level of an actual policy. Administrative Policy Statement 12.4, “Animal Use”, is a combination of policy and procedure originally housed in the now defunct Operations Manual and rolled into the new Administrative Policy Statements. Both versions now are part of the UW Policy Directory with APS 12.4 restating EO 53 as its introduction. David Anderson and Mary Lidstrom were consulted and agreed that combining the information, minus the procedure, into the executive order would be an appropriate way to address the redundancy. The executive order was chosen over keeping the APS in order to maintain the 60 day faculty senate review. Upon final approval of EO 53, APS 12.4 will be rescinded in a separate process. Attachments Please find the following documents attached for your review, comment and action:
• EO 53 Animal Use with client changes – 10-15-18 clean draft • EO 53 draft with tracked changes of proposed amendments • Action item – Upon completion of review, please date and sign the “Approval and Routing
Process” table on the “EO 53 Transmittal Letter President Approved for 60 day review” Please find the following documents attached for your reference:
Exhibit 3
• A copy of APS 12.4, “Animal Use” as it is currently published in the UW Policy Directory. • Policy Proposal Intake Form for APS 12.4 and EO 53- this document kickoffs the policy
development process and provides additional background information from the responsible office regarding amending/updating the order.
Thank you for your review and comment. Sincerely,
Barbara Lechtanski Director of Rules Coordination Executive Office of the President and the Provost
Exhibit 3
University of Washington D R A F T
Presidential Orders
Executive Order No. 53
Animal Use
1. PolicyPurpose
The University assumes responsibility for the humane treatment of animals used in research, teaching, and other activities. The institution is guided by principles, laws, and regulations set forth by local, state, and federal governments. Compliance with these regulations is required by University units involved in the use of animals. University of Washington assumes responsibility for the humane treatment of animals used in research, teaching, and other activities. The institution is guided by laws and regulations set forth by the Federal government. Compliance with these regulations is expected of the various University units involved in the use of animals. To assist in such compliance and to ensure humane treatment of animals, the Institutional Animal Care and Use Committee (IACUC), appointed by the Executive Director for Health Sciences Administration, periodically inspects the animal facilities of the University, evaluates the care of animals in the context of regulations, and reports to the Executive Director for Health Sciences Administration on a semiannual basis (Executive Order No. 53).
2. Definitions
AAALAC—AAALAC, International (an independent accrediting organization) AV—Attending Veterinarian DCM—Department of Comparative Medicine IACUC—IInstitutional Animal Care and Use Committee IO—Institutional Official OAW—Office of Animal Welfare PHS—US Public Health Service USDA—US Department of Agriculture WaNPRC—Washington National Primate Research Center
3. The Institutional Official
The Institutional Official is the individual in the organization having the administrative and operational authority to commit institutional resources to ensure that the animal care and use program complies with requirements of the Animal Welfare Act and PHS Policy.
24. The Institutional Animal Care and Use Committee
The Institutional Animal Care and Use Committee (IACUC), appointed by the Institutional Official, pre-approves all proposals to use vertebrate animals in teaching, testing, or research, ensures that all individuals working with animals are properly trained, periodically inspects the animal facilities of the University, evaluates the University's animal care and use program in the context of the policies and regulations, reviews concerns involving the animal care program, and reports to the Institutional Official on a semiannual basis.
Exhibit 4
EO No. 53 09/05/18 Page 2
Institutional Animal Care and Use Committee (IACUC) is appointed by the Executive Director for Health Sciences Administration, under authority delegated from the President, to oversee and make recommendations to University officials regarding the institution's use of animals. Committee activities include:
• Review of the animal care and use program.
• Inspection of all animal housing and use areas (including laboratories).
• Review of concerns presented involving the animal program.
• Review, approve, require modifications for approval, or withhold approval of proposed use of animals in teaching, testing, and research.
• Review and monitor animal use in progress and suspend studies not performed as approved or not in compliance with regulations.
• Ensure all personnel performing animal use procedures are properly trained.
The Association for Assessment and Accreditation of Laboratory Animal Care, International (AAALAC) is the voluntary, nongovernmental organization for accreditation of laboratory animal care facilities and programs. Continuing AAALAC accreditation for the entire campus is a goal for the University. The standards by which AAALAC judges animal programs are set forth in the Guide for the Care and Use of Laboratory Animals, published by the Institute of Laboratory Animal Resources (ILAR), National Research Council. These standards constitute the primary set of guidelines for animal care and use at the University.
3. Policy for Obtaining Animals
The University's policy, based on federal U.S.D.A. regulations, is that all nonhuman primates must be procured through the Regional Primate Research Center (RPRC), and other animals must be procured through the Department of Comparative Medicine, irrespective of use (teaching or research), funding source, or school/college involved. This procurement policy complies with federal regulations, implements a preventive medicine program that includes the certification of suppliers based on the health status of their animals, and makes certain that space, caging, and care meet accreditation standards prior to the receipt of animals.
45. Attending Veterinarian
The University The Attending Veterinarian (AV) is charged to establish and maintain a program of appropriate veterinary care. The AV or his/her designee has final authority regarding the health and welfare of the animals at the University, the necessity for and components of treatments administered, and the necessity for euthanasia. Regulations require consultation with the AV or designee regarding the design of all studies involving more than momentary or slight pain or distress.Attending Veterinarian (UAV) is charged to establish and maintain a program of adequate veterinary care. The UAV or his or her designee has final authority regarding the health and welfare of the animals used in University protocols, the necessity for and components of treatments administered, and the necessity for euthanasia. Regulations require consultation with the UAV or his or her designee regarding the design of all studies involving more than momentary pain.
Exhibit 4
EO No. 53 09/05/18 Page 3
6. Accreditation
The University animal use program is PHS assured and USDA registered. In addition, the University expectsis committed to continuing AAALAC accreditation for the entire campus and program. AAALAC International is the voluntary, nongovernmental organization for accreditation of laboratory animal care facilities and programs. The standards by which PHS, USDA, and AAALAC judge animal programs constitute the primary set of guidelines for animal care and use at the University.
7. Obtaining Animals
All vertebrate animals used in teaching, testing or research must be procured through appropriate mechanisms — nonhuman primates through WaNPRC, and all other species through DCM — irrespective of use, funding source, or school/college involvedThis procurement policy complies with federal regulations, implements a preventive medicine program that includes the certification of suppliers based on the health status of their animals, and makes certain that space, caging, and care meet accreditation standards prior to the receipt of animals. The IACUC may approve exceptions, such as for wildlife studies.
58. Departmental Animal Facilities
All animal facilities (terrestrial and aquatic) must be approved by the AV and the IACUC prior to their use. All facilities are regularly inspected to ensure compliance with regulations, adequate veterinary care, and the humane care of animals. The WaNPRC and DCM are responsible for all all animal facilities maintaining terrestrial species; the IACUC may approve exceptions..
Several departments maintain their own animal facilities. The animal care program of each facility is responsible to the Executive Director for Health Sciences Administration through the UAV. The departmental facilities must be approved by the UAV and are regularly visited by Department of Comparative Medicine personnel and IACUC members to ensure compliance with regulations, adequate veterinary care, and the humane care of animals.
69. Hazardous Agents and Conditions
Occupational health and safety must be ensured. Animal work involving potentially hazardous conditions or the use of hazardous agents on animals must comply with the requirements of the applicable University oversight entities, such as the Environmental Health & Safety Department, the Embryonic Stem Cell Research Oversight Committee, and the Institutional Biosafety Committee.
The use of hazardous agents on animals must be approved by and comply with the requirements of the pertinent University committee: Biohazard Committee, Chemical Agent Safety Committee, Radiation Safety Committee, or Recombinant DNA Committee.
710. Animal Care Concerns
Any University staff or member of the public who becomes aware of what he or she believes to be an abuse of animals used in a University teaching or research program has a responsibility and right to notify the IACUC and have the concern/complaint investigated. An individual reporting a suspected animal welfare concern need not identify him/herself to make a report. In person, telephonic and electronic mechanisms for reporting concerns are availableUniversity staff or member of the public who becomes aware of what he or she believes to be an abuse of animals used in a University teaching or research program has a responsibility and right to notify the IACUC and have the concern/complaint
The IACUC and/or the UAV will investigate reported concerns.
11. Responsible Office and Additional Information
The Office of Animal Welfare (OAW) is tasked with supporting the Institutional Official, the IACUC, the AV, and the University community in ensuring the humane treatment of animals and compliance with applicable laws and regulations. OAW can be contacted at http://oaw.washington.edu or [email protected]. Further information regarding the care and use of animals is contained in the Department of Comparative Medicine's Information Manual. For information regarding use of nonhuman primates, contact the Director of the RPRC. at:
Phone: 206-543-1430
Campus mail: Box 357330
12. History (This section is for Rules Coordination Office use only for the history of creation and revision to the order.)
May 1, 2002; formerly Administrative Policy Statement 12.4 recodified and revised October xx, 2018.
The University of Washington assumes responsibility for the humane treatmentof animals used in research, teaching, and other activities. The institution isguided by laws and regulations set forth by the federal government.Compliance with these regulations is expected of the various University unitsinvolved in the use of animals. To assist in such compliance and to assurehumane treatment of animals, the Institutional Animal Care and UseCommittee (IACUC), appointed by the Executive Director for Health SciencesAdministration, periodically inspects the animal facilities of the University,evaluates the care of animals in the context of the regulations, and reports tothe Executive Director for Health Sciences Administration on an semiannualbasis.
December 4, 1975; October 6, 2000.
For related information, see:
Executive Order No. 8, "Classified, Proprietary, and Restricted Research"Executive Order No. 26, "Internal Support of Graduate Study andResearch"Executive Order No. 34, "Grant and Contract Support of UniversityActivities"Administrative Policy Statement 12.4, "Animal Use"
(Approved by the Vice President for Medical Affairs by authority of Executive Order No. 6)
1. Policy
The University of Washington assumes responsibility for the humane treatment of animals used inresearch, teaching, and other activities. The institution is guided by laws and regulations set forthby the Federal government. Compliance with these regulations is expected of the various Universityunits involved in the use of animals. To assist in such compliance and to ensure humane treatmentof animals, the Institutional Animal Care and Use Committee (IACUC), appointed by the ExecutiveDirector for Health Sciences Administration, periodically inspects the animal facilities of theUniversity, evaluates the care of animals in the context of regulations, and reports to the ExecutiveDirector for Health Sciences Administration on a semiannual basis (Executive Order No. 53).
2. The Institutional Animal Care and Use Committee
The Institutional Animal Care and Use Committee (IACUC) is appointed by the Executive Directorfor Health Sciences Administration, under authority delegated from the President, to oversee andmake recommendations to University officials regarding the institution's use of animals. Committeeactivities include:
Review of the animal care and use program.
Inspection of all animal housing and use areas (including laboratories).
Review of concerns presented involving the animal program.
Review, approve, require modifications for approval, or withhold approval of proposed use ofanimals in teaching, testing, and research.
Review and monitor animal use in progress and suspend studies not performed as approvedor not in compliance with regulations.
Ensure all personnel performing animal use procedures are properly trained.
The Association for Assessment and Accreditation of Laboratory Animal Care, International(AAALAC) is the voluntary, nongovernmental organization for accreditation of laboratory animalcare facilities and programs. Continuing AAALAC accreditation for the entire campus is a goal forthe University. The standards by which AAALAC judges animal programs are set forth in the Guidefor the Care and Use of Laboratory Animals, published by the Institute of Laboratory Animal
Resources (ILAR), National Research Council. These standards constitute the primary set ofguidelines for animal care and use at the University.
3. Policy for Obtaining Animals
The University's policy, based on federal U.S.D.A. regulations, is that all nonhuman primates mustbe procured through the Regional Primate Research Center (RPRC), and other animals must beprocured through the Department of Comparative Medicine, irrespective of use (teaching orresearch), funding source, or school/college involved. This procurement policy complies withfederal regulations, implements a preventive medicine program that includes the certification ofsuppliers based on the health status of their animals, and makes certain that space, caging, andcare meet accreditation standards prior to the receipt of animals.
4. Attending Veterinarian
The University Attending Veterinarian (UAV) is charged to establish and maintain a program ofadequate veterinary care. The UAV or his/her designee has final authority regarding the health andwelfare of the animals used in University protocols, the necessity for and components oftreatments administered, and the necessity for euthanasia. Regulations require consultation withthe UAV or his/her designee regarding the design of all studies involving more than momentarypain.
5. Departmental Facilities
Several departments maintain their own animal facilities. The animal care program of each facilityis responsible to the Executive Director for Health Sciences Administration through the UAV. Thedepartmental facilities must be approved by the UAV and are regularly visited by Department ofComparative Medicine personnel and IACUC members to ensure compliance with regulations,adequate veterinary care, and the humane care of animals.
6. Hazardous Agents
The use of hazardous agents on animals must be approved by and comply with the requirements ofthe pertinent University committee: Biohazard Committee, Chemical Agent Safety Committee,Radiation Safety Committee, or Recombinant DNA Committee.
7. Animal Care Concerns
Any University staff or member of the public who becomes aware of what he or she believes to bean abuse of animals used in a University teaching or research program has a responsibility andright to notify the IACUC and have the concern/complaint investigated. Concerns involving animalcare and use at the University can be brought to the attention of the Executive Secretary of theIACUC at:
The IACUC and/or the UAV will investigate reported concerns.
8. Additional Information
Exhibit 6
10/17/2018
3/3
Further information regarding the care and use of animals is contained in the Department ofComparative Medicine's Information Manual. For information regarding use of nonhuman primates,contact the Director of the RPRC at:
Phone: 206-543-1430Campus mail: Box 357330
May 1, 2002.
Exhibit 6
Changing demographics of scientific careers: The riseof the temporary workforceStaša Milojevi!ca,1, Filippo Radicchia, and John P. Walshb
aCenter for Complex Networks and Systems Research, School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN 47401;and bSchool of Public Policy, Georgia Institute of Technology, Atlanta, GA 30332
Edited by Paul Trunfio, and accepted by Editorial Board Member Pablo G. Debenedetti May 8, 2018 (received for review February 16, 2018)
Contemporary science has been characterized by an exponentialgrowth in publications and a rise of team science. At the same time,there has been an increase in the number of awarded PhD degrees,which has not been accompanied by a similar expansion in thenumber of academic positions. In such a competitive environment,an important measure of academic success is the ability to maintaina long active career in science. In this paper, we study workforcetrends in three scientific disciplines over half a century. We finddramatic shortening of careers of scientists across all three disciplines.The time over which half of the cohort has left the field has shortenedfrom 35 y in the 1960s to only 5 y in the 2010s. In addition, we find arapid rise (from 25 to 60% since the 1960s) of a group of scientistswho spend their entire career only as supporting authors withouthaving led a publication. Altogether, the fraction of entering re-searchers who achieve full careers has diminished, while the class oftemporary scientists has escalated. We provide an interpretation ofour empirical results in terms of a survival model fromwhich we inferpotential factors of success in scientific career survivability. Cohortattrition can be successfully modeled by a relatively simple hazardprobability function. Although we find statistically significant trendsbetween survivability and an author’s early productivity, neither pro-ductivity nor the citation impact of early work or the level of initialcollaboration can serve as a reliable predictor of ultimate survivability.
scientific workforce | scientific careers | career success
Contemporary science has been characterized by an expo-nential growth in practitioners and publications (1) and a rise
of team science, both in terms of the increasing prevalence ofteam-authored work and the growth of team sizes (2–4). Thegradual shift from individual to team science is driven by a varietyof factors, including increasing capital intensivity of science (5) andthe increased need for technicians and staff scientists (6). At thesame time, there has been a substantial growth in the number ofawarded PhD degrees in recent decades (7), which has not beenaccompanied by a similar increase in the number of academicpositions (8), leading to concerns about the lack of opportunitiesfor new PhDs in science (9, 10) and even warnings regardingpossible scientific workforce bubbles (11, 12). In an environmentwith substantial growth in PhDs granted and only modest growth inthe number of faculty positions, the idea of each professor regularlyreproducing himself or herself in each cohort of graduate studentsbecomes untenable. These and similar data have led to calls forrethinking academic careers, and to discussions of the need forpolicy interventions to address this growing problem (5, 9, 13).How does the shifting landscape of science over the past half-
century affect the roles of new researchers and their overall ca-reers? There is an abundance of studies that focus on the criteriathat may affect researchers’ success in terms of the impact of theirwork, especially in terms of citations to publications. However,another, and perhaps more fundamental, aspect of success is theability to perform research over the full extent of someone’s ca-reer, rather than leaving the field prematurely. A smaller fractionof literature focuses on understanding the factors leading to suc-cessful academic careers in this broader sense and, more recently,the factors contributing to abandoning scientific careers (14–16).
Prior work has identified productivity (14, 16–20), impact (20, 21),number of collaborators (14, 17), gender (22), prestige of PhDgranting and hiring institutions (23, 24), prestige of the advisors (24,25), gender of the advisors (16), and level of specialization (26) asimportant factors correlated with career success. Some of thesestudies have found that these factors are correlated. For example,there is a correlation between the citation success of early papers andlater increase in productivity (27). There is also a reported correla-tion between gender and productivity (19, 28, 29), gender and cita-tions, and gender and collaboration. Finally, there is a correlationbetween institutional prestige and productivity (30, 31), as well asinstitutional prestige and impact (32). Directionality of these corre-lations is difficult to establish and is not the focus of this paper.On the other hand, there are relatively few studies that focus on
modeling scientific careers (30, 33–38) in the context of surviv-ability. An early study of this type (35) used a sample of 500 au-thors during the period 1964–1970 and has established a division ofall authors into transient and continuants and found that the levelsof productivity are correlated with career length. Two recent studies(36, 37) used survival analysis and hazard models to examine genderdifferences in retention of science and social science assistant pro-fessors. These studies established that the chances of survival ofassistant professors in science and engineering are less than 50%;that the “median time to departure is 10.9 y” (36); and that, in socialsciences, “half of all entering faculty have departed by year 9” (37).Despite various efforts, there is a clear gap in our knowledge of
careers of the scientific workforce in general (and not only tenure-track scientists). Furthermore, large-scale investigation of the trendsin careers of the scientific workforce across entire disciplines andover long periods of time (many decades) is still in its infancy.In this study, we analyze the changing careers of the scientific
workforce of entire disciplines without making assumptions re-garding the positions individuals comprising the workforce havein the scientific community (i.e., not limited to those who havetenure track jobs, as was the case in many of the earlier studies).We specifically focus on the role that different authors play inknowledge production. Furthermore, we investigate whether onecan identify early factors (during a researcher’s apprenticeshipphase) that would indicate a scientist’s ability to maintain a
This paper results from the Arthur M. Sackler Colloquium of the National Academy of Sci-ences, “Modeling and Visualizing Science and Technology Developments,” held Decem-ber 4–5, 2017, at the Arnold and Mabel Beckman Center of the National Academies ofSciences and Engineering in Irvine, CA. The complete program and video recordings ofmost presentations are available on the NAS website at www.nasonline.org/modeling_and_visualizing.
Author contributions: S.M., F.R., and J.P.W. designed research; S.M. and J.P.W. performedresearch; S.M. analyzed data; and S.M., F.R., and J.P.W. wrote the paper.
The authors declare no conflict of interest.
This article is a PNAS Direct Submission. P.T. is a guest editor invited by theEditorial Board.
Published under the PNAS license.1To whom correspondence should be addressed. Email: [email protected].
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1800478115/-/DCSupplemental.
research-active career over many years. Our big-data approachis facilitated by an extensive longitudinal dataset containingmillions of bibliographic items covering the entire period ofcontemporary science.To capture the above-stated changes in the demographics of the
scientific workforce, we created a survival model of authors basedboth on the primary role they play in the production of knowledgeand their ultimate survival status in science. Each author is placedin one of two categories based on his or her primary authorshiprole: lead authors and supporting authors. Lead authors are allauthors who have led a publication at any time in their career,whereas supporting authors are the ones who have never had thatrole in their career. Furthermore, we place each author (whetherlead or supporting) into one of the five categories in terms of his orher ultimate survival status: transients (authors with a single pub-lication), junior dropouts (multipaper authors leaving after 0–10 yafter the first publication), early-career dropouts (multipaper au-thors leaving after 11–15 y after the first publication), midcareerdropouts (multipaper authors leaving after 16–20 y after the firstpublication), and full-career scientists (multipaper authors whohave careers longer than 20 y). This classification is presentedschematically in Fig. 1. The balance between supporting and leadauthors in each of the survival categories is different, as indicatedby the tilted curve in Fig. 1. Most transient scientists belong to thesupporting author group, whereas as we move toward the full-career status, the proportion shifts in favor of lead authors. Tostudy the changing landscape of scientific careers in terms ofknowledge production roles and survivability, we focus our analysison cohorts: a group of authors who first appear on the scientificstage at the same time (in the same year). Our study is facilitated bythe availability of extensive longitudinal data allowing us to followup half a century of cohorts and to assess their eventual careers.In this study, we focus on researcher cohorts in three scien-
tific disciplines covering different areas of science: astronomy(physical sciences), ecology (life sciences), and robotics (engi-neering and computer science). We focus on researchers whohave published in principal journals belonging to these fields(listed in SI Appendix). These are the journals that are wellestablished, usually publish a large fraction of original researchin a particular field, and are considered to be good representa-tives of those fields. We used a number of studies to identify thecore journals. For astronomy, we used the list of core journalsprovided in ref. 39; for ecology, we used the lists provided in refs.40, 41. We define authors and derive their metrics from principaljournals alone. Some of these authors may publish some fraction
of their work in other journals (either other journals in the same ora related area or, in some cases, in multidisciplinary journals). Thisincompleteness will reduce the metrics and, in some cases, mayaffect the determination of career length or authorship role.Quantifying the incompleteness and its effects is difficult, given thelack of topical classification at the article level. However, since theanalyses in the paper are relative (i.e., one time period vs. another,authors with one set of characteristics vs. another), the in-completeness will not affect some time periods or authors morethan the others; thus, the relative trends should be unaffected. Ourchoice is conservative because the alternative, including all worksthat match some name, would greatly exacerbate the name disam-biguation problem and potentially confound the results.All of the analyses are derived from the bibliographic data
extracted from the full Clarivate Analytics Web of Science da-tabase. We used the entire temporal span of the database (from1900 to 2015) to establish the starting and ending years of activityof each author, and thus to identify the cohorts. For astronomyand ecology, we follow cohorts from 1961, and for robotics, wefollow cohorts since 1985 (none of the core robotics journalspublished before 1983). The number of authors belonging tothese cohorts and included in the analysis is 71,164 in astronomy,20,704 in ecology, and 17,646 in robotics.To identify unique authors, we perform, for each field-specific
dataset separately, disambiguation of author names using the hy-brid initials method. The scheme represents an improvement overstandard initials methods because it either ignores or takes intoaccount the middle initial depending on the name frequency (42),minimizing the splitting of unique authors due to inconsistent useof the middle initial while maximizing the author separation.Percentages of authors whose identity has been compromised dueto either splitting or merging have been estimated by simulationand are between 3% and 5% (42), which is below a level thatwould significantly affect our results. Ambiguity is relatively lowbecause we focus on principal journals alone.The roles that authors play in knowledge production (lead and
supporting) are established from author lists in the following way.Authors on single-authored papers are given a lead author status. Toestablish the roles in multiauthored papers, we have first verified thatthe author lists are ordered by author contributions (with the firstauthor almost always matching the corresponding author) in allthree disciplines under study, except in rare cases when they areordered alphabetically. We find no evidence for a deliberate al-phabetical listing in papers with fewer than approximately four au-thors, and in such cases, we adopt the first author as a lead author.For longer lists of authors, we check if the author list is alphabetical(based on up to seven first-listed authors), and if it is not, we againtake the first listed author as a lead author. If the list is alphabetical,we determine the lead author only if the corresponding author is notthe first author. The fraction of articles for which the lead authorcould not be determined is relatively small (1.6%, 0.2%, and 0.3%for astronomy, ecology, and robotics, respectively).For each unique author, we establish the cohort year as the year
when he or she first appeared as an author in any role (lead authoror supporting author). Since our data extend to periods before thestarting time for the analysis, the cohort year, as well as the year ofthe departure from the field, can be established reliably. An au-thor is considered currently active if he or she has published (inany role) in the last 3 y covered by database. Of the active authors,some have achieved full-career status (defined as at least 20 y ofactive publishing), whereas for others, their ultimate survival statusis currently unknown and they are excluded from those analyseswhere such information is required.
ResultsGrowth of Supporting Author Scientists. Previous results on thegrowth of team science and the changing structure of such teamsallow us to propose that one component of the changing career
Fig. 1. Model of scientific careers. For each cohort of authors entering thefield, we determine the knowledge production role as a “lead author” (re-searcher who leads the production of a scientific publication at any time inhis or her career) or a “supporting author” (those who will never lead theproduction of a scientific publication). Furthermore, each new author willfall into one of five categories of ultimate career status: transients (authorswho only had one publication), dropouts (authors who leave the field pre-maturely at different levels of their careers), and full-career scientists (au-thors who ultimately survive in the field). In each survival category, there willbe some authors classified as lead and some as supporting (the repeated redcurve). We follow 50 cohorts starting from the 1960s.
Milojevi!c et al. PNAS | December 11, 2018 | vol. 115 | no. 50 | 12617
demographics of scientist is a differentiation into heterogeneouscareer paths, with some scientists becoming lead authors andothers specializing as nonlead supporting team members. Here,we establish the extent to which each of these groups has con-tributed to the creation of knowledge over the past half-century.Fig. 2 shows the fraction of authors from each cohort that, at any
point in their career, will contribute to the field as lead authors.The fraction of lead authors has been experiencing a dramaticdownward trend in all three disciplines since the 1960s, leading to acomplementary increase in the share of supporting authors. Fur-thermore, the proportion of lead authors has been similar in allthree fields, indicating that the shift of roles may follow a universalpattern. While in the early cohorts, from the 1960s and 1970s, thevast majority (∼75%) of entering authors had a lead author role,this percentage has dropped to less than 40% in most recent co-horts. The strong shift is unrelated to the presence of transientauthors. If those were excluded from the cohort, the drop in theshare of lead authors remains similar: from ∼85% in the 1960s to∼50% in the current decade. Is the increasing fraction of sup-porting authors an inevitable outcome of increasing team sizes? Totest this possibility, we performed modeling in which we wentthrough all of the papers in each dataset and tried to replace thecoauthors (all authors except the lead author) who are classified assupporting authors with the authors who have the status of beinglead authors and were active at the time of paper publication. Inthis modeling, the number of authors per paper remains the same,as well as the individual (lead author) productivity (because weonly replace coauthors), yet we were able to populate mock authorlists solely with lead authors. This demonstrates that having largeteam sizes does not automatically require the recruitment of sup-porting scientists. It also signifies that large teams are not entirelythe product of collaboration among eventual full-role scientists(which may be more prevalent in small teams) but rather involvethe recruitment of a special workforce of supporting scientists.
Survival Function and the Decreased Half-Life of Cohorts. The min-imal level of contribution to scientific knowledge is the pro-duction of a single paper. The existence of such authors was firstpointed to by Price and Gürsey in 1976 (35), who named this type
of author “transients” and established that they accounted for 25%of the population of scientists in the late 1960s. In Fig. 3, we findthat the fraction of transients has remained relatively constant inmost cohorts, although this category of authors has started to in-crease in recent cohorts across all three fields (since about the1990s), especially in robotics and ecology. Notably, we also find that,unlike the fraction of lead authors, which is universal, the number oftransients is field-dependent, with levels in astronomy similar to theones Price and Gürsey (35) found and much higher rates (50–70%)in ecology and robotics. Interestingly, one-quarter of recent tran-sients in all three fields were lead authors. This fraction was as highas one-half in the 1960s. This suggests that the threshold for leadauthorship is often crossed even in the population that never gen-uinely embarks on a research path in that discipline.For authors who persist after the initial publication, we employ
survival analysis to study their scientific career longevity. In Fig. 4,we show the survival curves of select cohorts spanning the periodof the most recent four decades. Survival curves are calculated asthe fraction of a cohort remaining after x years. While the survivalcurves of contemporaneous cohorts in different fields have dif-ferent slopes, we see that the curves undergo a similar evolution ineach field: from relatively long survival times in the 1980s to veryrapid attrition of the scientific workforce in most recent times. Weobserve that until the 1980s (1990s for astronomy), more than halfof each cohort had “full” (20+ y) careers. However, in recentdecades, this is no longer the case. The results correspond to acontinuous decline in the expected career length.To expand the survival analysis to every cohort and to cover
the full period from 1961, we calculate, for each cohort, its “half-life,” the time it takes to lose 50% of the cohort. Half-lives aredetermined from a linear fit to the survival function, regardlessof whether the cohort has yet reached 50%. Half-lives for thethree fields as a function of cohort year are shown in Fig. 4D. Inastronomy, the half-life has dropped from about 37 y in 1960s tojust 5 y in 2007. In ecology and robotics, the half-lives are evenshorter and have also been decreasing at similar rates. When weanalyze lead authors and supporting authors separately, we findthat in ecology and robotics, their half-lives are similar, whereasin astronomy, the half-lives of supporting authors are shorter
0.00.10.20.30.40.50.60.70.80.91.0
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AstronomyEcologyRobo!cs
Fig. 2. Fraction of each cohort that contributes to or will contribute to theknowledge production as lead authors. The status of lead author means thatthe author has led a publication at any time in his or her career. An in-creasing fraction of entering authors never acquire the lead role but par-ticipate in knowledge production solely as supporting scientists.
0.00.10.20.30.40.50.60.70.80.91.0
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Fig. 3. Fraction of each cohort that has published only one paper (transientauthors). The share of transients has increased in the past two decades, espe-cially in ecology and robotics. The trend in the fraction of authors who are leadauthors (Fig. 1) remains similar when transients are excluded from cohorts.
12618 | www.pnas.org/cgi/doi/10.1073/pnas.1800478115 Milojevi!c et al.
than those of the lead authors by about 5 y. Most recently (2010cohort) half-lives are 9 and 4 y, respectively.
Career Progression Model. To pave the way for a more funda-mental understanding of the processes that lead to the attritionof the workforce, we describe the career trajectory of an indi-vidual researcher using a simplified version of the model shown inFig. 1. In the simplified version, we focus only on nontransientauthors. Further, we neglect the difference among types ofdropouts. During a career, a researcher can be in one of the fol-lowing four states: B, the beginning of a career (defined with thefirst paper); S, achievement of the supporting author role; L,achievement of the lead author role; and X, cessation of the ca-reer. An author can initially be in the S state and transition intothe L state. The S → L transition is considered irreversible (i.e.,L→ S is not allowed in the model). Authors continue in their statesuntil reaching state X. We train the model using the data at ourdisposal. We find that the S → L transformation takes place in thefirst 5 y of a career: Authors who become leads achieve this status
quickly. For the survival model, we are interested in the likelihoodof observing the transition S → X or L → X (i.e., the hazardprobability). We show the hazard probability in Fig. 5 sepa-rately for lead and supporting authors. For lead authors, thehazard probability is relatively constant, at around 0.03. Forsupporting authors, the exit probability is higher and shows atwo-mode behavior: a decrease in the first 8 y and reaching amore stable value subsequently. We model the hazard function asa piece-wise linear + constant function:
h= aðt− tbreakÞ+ b for t≤ tbreak, and h= b= const. for t> tbreak,
where a and b are constants and tbreak = 8 is the time where thehazard function changes behavior. For astronomy, the model istested against the data (Fig. 5C). The survival curves are nowbased on all cohorts, so they represent time-averaged survival forlead and supporting authors. The model reproduces the sa-lient features of the empirical curve. Remarkably, the analysisshows that the hazard is relatively constant throughout the career
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Fig. 4. Survival functions of select cohorts in three fields (A–C) and the half-life (time needed for half of the cohort to abandon the field) of all cohorts fromall three fields (D). The decline in survivability over the past half-century has been remarkable.
0.000.020.040.060.080.100.120.140.160.180.20
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Fig. 5. Hazard model. Hazard probabilities for lead authors (A) and supporting authors (B). (C) Comparison of the linear + constant hazard model (dottedlines) with the empirical survival functions in the field of astronomy (AST).
Milojevi!c et al. PNAS | December 11, 2018 | vol. 115 | no. 50 | 12619
SOCIALSC
IENCE
SCO
LLOQUIUM
PAPE
RExhibit 7
(i.e., that there are no punctuated bottlenecks at which a largefraction of a cohort would leave the field).
Early Indicators of Scientific Survivability. Given the increasinguncertainty of achieving a full career in science, one wonderswhether there are any characteristics of scientists early in theircareers that could indicate their survival status (38). We define“early” as the first 5 y of a researcher’s presence in the field(what we might call his or her “apprenticeship” years). Given ourfocus on the roles that scientists play in the production ofknowledge, we focus on the variables that are directly related tothis process: productivity, impact, and collaboration. These var-iables have been identified in prior work as correlated with ca-reer trajectories. We do not focus on some other variables thathave been identified as important for career longevity and suc-cess, such as gender and the prestige of an institution a scientistis affiliated with, which are more pertinent in the context of studiesthat focus on career aspects that involve institutional and job roles(hiring, tenure, and promotion). While our models do not explicitlycontrol for gender, two recent studies analyzing career longevity ofacademic faculty found no differences in faculty attrition by gender(except in the field of mathematics) since 1990 (36, 37).In this analysis, we look at the total productivity in the first 5 y of
a career (in any authorship role) and examine two types of impact:average impact of early work (the number of citations per paperreceived in the first 5 y) and the peak impact (the maximum numberof citations received in a 5-y window to a single, early-career pub-lication). Finally, for collaboration, we focus on the number of di-rect collaborators in the first 5 y of the career. Direct collaboratorsare defined as coauthors on a paper led by the author in question, aswell as all of the unique lead authors of papers on which the authorin question is a coauthor. If neither author is a lead author on somepublication, such authors do not constitute direct collaboration.To aggregate the data from cohorts that span a long time
period, one needs to take into account that all three variableshave significantly increased over time. For example, a researcherfrom the 1960 cohort who had 10 citations per paper may havebeen the most impactful in that cohort (∼100 percentile),whereas the same number of citations for a cohort from 2000may place the researcher in middle of the cohort (∼50 percen-tile). Therefore, we establish normalized measures by de-termining the percentiles for each variable and for each author ina given cohort.Fig. 6 shows mean productivity, citation, and collaboration
levels for authors of different survival categories: junior drop-outs (J; leaving 6–10 y after the first publication); early-career
dropouts (E; 11–15 y); midcareer dropouts (M; 16–20 y); and,finally, the scientists who achieved full careers (F; >20 y). Thevalues for robotics, which contains fewer cohorts and a smallersample size, is noisier, and we omit it for clarity. The trends areshown separately for lead and supporting authors. The trends arefairly consistent between astronomy and ecology (with the ex-ception of collaboration). Furthermore, we find that the trendsinvolving average number of citations per paper and maximumnumber of citations are very similar, and we show only the onesinvolving average number of citations. Fig. 6 reveals that leadand supporting authors follow different trends. Overall, leadauthors, regardless of survival category, have significantly higherproduction and collaboration levels than supporting authors,whereas their impact levels are similar. Supporting authors, whileworking on fewer papers and with fewer direct collaborators,nevertheless contribute to projects of similar impact. For leadauthors, there is a slight positive trend between the early level ofall three metrics and eventual survival (except for ecology andcollaboration, where there is no significant trend). In particular,based on the means comparisons, lead researchers who go on tofull careers (F) tend to have, on average, higher levels of pro-ductivity, citation, and (for astronomy) collaboration.The four-state career model, which provides an estimate of the
career termination hazard rate by career state, not only supportsthe empirical survival functions well but shows that the hazardrate is relatively constant throughout a career, thus also sup-porting the model developed by Petersen et al. (34).The above plots focused on individual variables. To quantify the
effect of the variables on survival taking into account internal cor-relations, we use the Cox proportional hazard survival model. For thisanalysis, we use career lengths in annual increments (rather thangrouping into only four categories) and the Efron method to correctfor ties. Although many of the cases include careers of greater than20 y, we recode career length as maximizing at 20 y (hence, all careersgreater than 20 y, corresponding to full-career survival status, aretreated as right-truncated). In addition, because we are testing theeffects of the first 5 y of performance on subsequent exit, all our casesin this analysis have career lengths of at least 6 y. We are then testing,among the set of researchers who accumulate 5 y of backgroundexperience, how career lengths differ by publications, citations, andnumber of collaborators during their first 5 y (net of the effects of theother variables). We use the untransformed publications and citationsdata, as we will be focusing on comparisons within cohorts.Given the very different survival curves for the lead and sup-
porting authors (Fig. 5), we estimate the effects separately foreach group. Tables 1 and 2 give the models. Column 1 in Tables 1
0
10
20
30
40
50
60
0 1 2 3 4 5
Prod
uc!v
ity(p
erce
n!le
)
Survival category
Early produc!vityand survival
AST lead authorsECL lead authorsAST suppor!ngECL suppo!ng
0
10
20
30
40
50
60
0 1 2 3 4 5
Colla
bora
tors
(per
cen!
le)
Survival category
Early collabora!onand survival
AST lead authorsECL lead authorsAST suppor!ngECL suppor!ng0
10
20
30
40
50
60
0 1 2 3 4 5
Cita
!on
(per
cen!
le)
Survival category
Early impactand survival
AST lead authorsECL lead authorsAST suppor!ngECL suppor!ng
J E M F J E M FJ E M FDROPOUTS
A B C
Fig. 6. Early predictors of survivability in astronomy (AST) and ecology (ECL). Normalized productivity (A), impact (B), and collaboration (C) metrics based onthe number of publications from the first 5 y of an author’s career are shown for lead (full lines) and supporting (dashed lines) authors in two disciplines forauthors of different survival status: junior dropouts (J; leaving after 6–10 y after the first publication), early-career dropouts (E; 11–15 y), midcareer dropouts(M; 16–20 y), and, finally, the scientists who achieved full careers (F; >20 y).
12620 | www.pnas.org/cgi/doi/10.1073/pnas.1800478115 Milojevi!c et al.
and 2 shows the effects of background characteristics (publications,citations, and number of collaborators) on hazards of exit (withvalues greater than 1 increasing the rate of exit and values less than1 decreasing the rate of exit). Table 1 shows the results for leadauthors, and Table 2 shows the results for supporting authors.Column 2 repeats this analysis using the maximum number of ci-tations among the researchers for the first 5 y of publications. Wesee that when we control for the net effects of the other indicatorsacross the 50 y (1960–2010) for lead authors, publications signifi-cantly reduce the hazard of exit, while there is little effect of cita-tions (either measure) or number of collaborators. For supportingresearchers, publications also have a negative effect on exit, al-though the effect is weaker than for lead authors. Citations (eithermeasure) also have an effect, although the effect is positive (in-creasing exit). The number of collaborators has no effect.A test of the proportional hazard assumption that the effects
of the predictors are constant over time rejects the null hy-pothesis for publications (and is close to significant for citations).Furthermore, the data above suggest that the career conditionsare changing over time and that publications, citations, andcollaborations rates have also been changing over time. Hence,we estimate the effects across cohorts separately (Tables 1 and 2,columns 3–7). For lead authors, we see that publications haveconsistently been a significant predictor of career longevity. We alsosee that citations reduced the hazard of exit in the early cohorts;however, more recently, the model is dominated by publications,with citations having little independent effect. In contrast, for sup-porting authors, publications have very weak effects until the mostrecent cohort. Table 3 shows that these effects are largely consistent
across fields, although we find that the effect of publications issignificant for supporting researchers in astronomy.In Tables 1 and 2, we report the hazard ratios from a multi-
variate Cox proportional hazard model. We are estimating therelative hazard to exiting, truncating at 20 y (so we are estimatingthe relative hazard of leaving academic publishing before 20 y). Thetable is reporting the change in the hazard ratio for exiting from aone-unit change in each variable, controlling for the effects of all ofthe other variables. These hazard ratios can be interpreted by esti-mating how far they are from 1.0. For example, for lead authorsacross all years, publications have a coefficient of 0.891 (Tables 1and 2, column 1). This means that one publication reduces thehazard of exit by about 11% (1.000–0.891 = 0.109). In terms of theprobability of achieving a full career, it grows gradually from 50%for authors with one early publication to 85% for authors with 20publications. In contrast, one citation reduces the hazard very little(0.1%). Therefore, for lead investigators, each publication hassubstantially more impact on survival than does each citation (about100-fold greater). In contrast, for supporting authors, one publica-tion reduces the hazard of exit by about 3% (1.000–0.966), whilecitations again have very little effect. However, looking across thecohorts, we see this effect for supporting authors is largely limited tothe most recent cohort (Tables 1 and 2, column 7). We can also seethat for the full span of cohorts (Tables 1 and 2, column 1), theeffect of publications for lead authors is much greater than that forsupporting authors (11% vs. 3%), and that when we compare acrosscohorts (Tables 1 and 2, columns 3–7), the effect of publications forreducing exit is stronger (the hazard ratio is lower) for lead authorsthan for supporting authors.
Table 1. Cox proportional hazard regressions, for lead authors, by cohort
Publication productivity, citations, and collaborators pertain to the first 5 y of an author’s career. Standard errors shown in parentheses. LR, likelihoodratio. ***P < 0.001; **P < 0.01; *P < 0.05.
Table 2. Cox proportional hazard regressions, for supporting authors, by cohort
Publication productivity, citations, and collaborators pertain to the first 5 y of an author’s career. Standard errors shown in parentheses. LR, likelihoodratio. ***P < 0.001; **P < 0.01; *P < 0.05.
Milojevi!c et al. PNAS | December 11, 2018 | vol. 115 | no. 50 | 12621
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DiscussionRecent work on the organization of science has focused on theinternal structures of research teams and has argued that onelikely outcome of this shift in the nature of scientific work hasbeen the growth of supporting scientists, whose careers dependon being members of such teams (6, 13). Less obviously, therehas also been a concomitant increase in high-stakes evaluationand competition for funding, increasing the emphasis on pro-ductivity (43–46). One solution to this new emphasis on pro-ductivity is increasing the division of labor (47, 48). The growthof scientific team sizes is being accompanied by a transition inthe organization of scientific work from craft to bureaucraticindustrial principles, with increased division of labor and standardi-zation of tasks (13, 49, 50). The result is a growth of scientists whosefunction is to support the projects that others are leading. Ourresults confirm this scenario, showing that an increasing frac-tion of entering authors never transition from a supportingauthor to lead author role. We also show that such a trend isnot an inevitable outcome of the increasing sizes of teams, perse, but arises due to the different roles that some authors nowhave in large teams compared with the roles that members ofsmaller teams have (team members vs. collaborators). In somefields, such as ecology and robotics, lead and supporting au-thors have similar half-lives, while in others, such as astronomy,the half-lives of supporting authors is significantly shorter.Of course, there are well-known productivity advantages from
organizing teams with a division of labor, and with having someteam members specializing in supporting roles (47). Hence, it isperhaps not surprising that science is shifting to larger teams,with more specialization, and that, increasingly, some scientistsare specializing in supporting roles. Note that we are not as-suming status or skill distinctions in our classification of leadand supporting authors (49). We are arguing that such sup-porting scientists are critical to the production of contemporaryscience (6). However, it is also the case that institutions, such asuniversities and funding agencies, build around these traditionalstatus distinctions, for example, between postdoctoral scientists andtenure track professors (6). However, our survival analyses suggestthat the criteria predicting longevity for supporting scientists are quitedistinct from those for lead researchers and it may not be appropriateto impose similar criteria on both groups when making decisionsabout who to hire or whose contract to renew. We argue there is aneed to reform career structures in universities to account for thechanging nature of the population composition and reproductioncycles in team science, with social insect colonies rather than parent-child reproduction as a more appropriate model.
While we cannot address this with our current data, we pointto a tension between the research production and teachingfunctions that academic laboratories provide (5, 12, 43, 49, 51).These two trends are bringing fundamental changes to scientificcareers, with decreasing opportunities for lead researcher po-sitions and increasing production of, and demand for, a scientificworkforce to fill positions as permanent supporting scientists.Together, these trends suggest downward pressure on careerlongevity (as more people exit the academic science labor force)and the growth of dependent supporting scientist positions tosupport the relatively shrinking share of lead researchers. How-ever, one concern is that such supporting scientist positions do notfit well with the employment system in most universities, which arestructured around a graduate apprenticeship, a short period ofpostdoctoral training, and then movement into a tenure track (andeventually tenured) professor position (5). Instead, these supportworkers may be relegated to a series of short-term postdoctoralcontracts or other forms of contingent academic work. While thetraditional model implies an up-or-out academic pipeline (withsignificant shares of the research workforce dropping out ofresearch-active academic positions at each stage), the growth ofpermanent supporting scientists may suggest an alternative careerpath that, while perhaps with shorter survival than the traditionallead researcher path, may be a growing share of the academiclabor force. Furthermore, such careers may be premised on adifferent set of criteria than is typically predictive of the careersurvival of lead researchers.Our findings show that the shift in the mode of knowledge
production from solo authors and small core teams (2) has co-incided with a differentiation in the scientific workforce in termsof their roles. The increased need for both the specializationand possession of specialized technical knowledge to manipulateincreasingly complex instrumentation and data has created an es-sential group of supporting contributors to knowledge. Unfortu-nately, the existing job roles and educational structures may not beresponding to these changes. Our results suggest that, while essen-tial, these supporting researchers are suffering from greater careerinstability and worse long-term career prospects in some fields.
ACKNOWLEDGMENTS. This work uses Web of Science data by ClarivateAnalytics provided by the Indiana University Network Science Institute andthe Cyberinfrastructure for Network Science Center at Indiana University.This work was supported by National Science Foundation Social, Behavioral& Economic Sciences (SBE) Office of Multidisciplinary Activities (SMA) Early-Concept Grant for Exploratory Research (EAGER) SMA-1645585. F.R. waspartially supported by National Science Foundation Grant SMA-1636636.
Table 3. Cox proportional hazard regressions, for lead and supporting authors, by field
Publication productivity, citations, and collaborators pertain to the first 5 y of an author’s career. Standard errors shown in parentheses. AST, astronomy;ECL, ecology; LR, likelihood ratio; ROB, robotics. ***P < 0.001; **P < 0.01; *P < 0.05.
12622 | www.pnas.org/cgi/doi/10.1073/pnas.1800478115 Milojevi!c et al.
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