MODELLING PUBLIC KNOWLEDGE AND
ATTITUDE TOWARDS GENETICALLY MODIFIED MAIZE
Introduction
Statement of the problem
Objectives
Methodology
Conclusion
Potential benefits of genetically modified food to developing
countries.
The variable nature of a community's attitude on issues of
science and technology.
Information dissemination and effect of its failure.
Public sensitization about the importance of using biotechnology
to improve food production.
The study sought to establish the associations between knowledge
as an independent variable and attitude as a dependent variable
using generalized linear model despite controlling for a range of
other important characteristics such as age, education and social class.
This research assess different ways on how knowledge and
attitude relate to adoption of genetically modified maize and apply
the logistic Model to explain the relationship between variables
from the data.
We expect to know the significance of knowledge on attitude
towards adoption of Genetically modified organisms.
Potential benefits of GM organisms to developing
countries.
The relationship between Consumer attitudes and general
socio-political attitudes on genetically modified foods.
Importance of knowledge and attitude in determining the
development of biotechnology on agricultural
commodities.
The contribution of information dissemination to Public
knowledge and attitude towards genetically modified
organisms.
The use of the deficit model to explain public negative attitude
towards biotechnology referring to public’s scientific
ignorance.
Reviewed properties of the past fitted models to determine the
goodness of the model.
Contingent valuation (cv) approach on acceptance of GM food
by the public.
Does knowlegde on biotechnology influence its adoption?
Does knowledge influence attitude of biotechnology?
Does both knowledge and attitude influence adoption of Gm
maize in the four counties?
General objective.
To model public knowledge and attitude towards genetically
modified maize and apply in Uasin-ngishu, Transzoia and Elgeyo
marakwet counties.
Specific Objectives
• To propose a model for public knowledge and attitude towards
genetically modified maize.
• To empirically study the properties of the proposed model.
• To apply the model on data collected in Uasin-ngishu,
Transzoia, and Elgeyo marakwet counties.
This study helps the public who are lacking a proper understanding of
the relevant facts, people who fall back on mystical beliefs and
irrational fears of the unknown. If one accepts this hypothesis, the
obvious implication for biotechnology policy is that public
information campaigns should be instigated to remedy the public’s
disenchantment with biotechnology.
The study will also benefit scholars who are utilizing survey
methods that consistently uncover the associations between
knowledge of and attitude towards science despite controlling
for a range of other important characteristics such as age,
education and social class and often should not choose to
ignore this finding that culture, economic factors, social and
political values and worldviews. This are all important in
determining the public’s attitude towards science and hence
broaden the scope of the study to justify the need of GM foods
to increase food security in the country.
This study used primary data which was collected from
farmers of Uasin-ngishu, Transzoia and Elgeyo-marakwet
counties in Kenya.
The data was acquired through a survey where a person was
required to fill a questionnaire and was given a small briefing
about GM maize and products before the questionnaire was
administered.
It contains knowledge and attitude variables towards GM
maize where attitude was represented by two variables willing
to adopt and willing to buy.
Public attitude on GM maize represented by willingness to
buy and willingness to adopt as dependent variables and
knowledge as independent variable was computed.
The model used gives the level of adoption of GM maize in relation to public knowledge.
The kind of data that were used in this study was dichotomous
and the most preferable model applied in this case was logistic
model because the outcome side of the regression equation
was constrained to be in the interval (0, 1).
In the model that is going to be applied,
Pi is assumed to be the probability of consumers accepting
GM maize.
Xij is the matrix of independent variables , where i denotes the
ith respondent, and j denotes the jth independent variable,
which is consisted of consumers’ personal characteristics such
as gender and age, his/her socio-economic variables.
Pi = F (Zi) = F (BXi') = 1/ [1+exp (-Zi)] …………….. (1)
where, F (Zi) is used to denote the value of logistic cumulative
density function (CDF) associated with each possible value of the
underlying index Zi, which equals to an unobserved index level for
the ith observation, and which can be formalized as equation (1)
because βXi' is a linear combination of the independent variables in
equation (1); β = (β0, β1.....βj) is a vector of parameters we will
estimate.
Willingness_adopt = 0
Knowledge_GM
Willingness_buy 0 1
0 30 17
1 13 15
Willingness_adopt = 1
Knowledge_GM
Willingness_buy 0 1
0 11 19
1 10 21
prop.table (table1)
Willingness_adopt = 0
Knowledge_GM
Willingness_buy 0 1
0 0.22058824 0.12500000
1 0.09558824 0.11029412
Willingness_adopt = 1
Knowledge_GM
Willingness_buy 0 1
0 0.08088235 0.13970588
1 0.07352941 0.15441176
After getting the summary of glm, it was clear that the
intercept and standard error of the intercept was 0.38425 while
that of the first variable was 0.1136 and for the second was
0.2137 respectively. The residual standard error is 0.4882. The
multiple R-squared was 0.6459 while adjusted R-squared was
0.5052 with a p-value of 0.01179. Looking at the model they
concluded that it was significant because the R-squared is
more than 0.5. Checking if the variables are significant, we
look at the Pr (>|z|) which is 5.936 2.4e-08 which is very
significant.
Hence the model is 1/exp(-0.3843+0.1136X1+0.2137X2)
Willingness_buy Knowledge_GM Willingness_adopt
0.0
0.2
0.4
0.6
0.8
1.0
The success of a GM crop program would depend on the
acceptability of its products by citizens, it was therefore
suggested not only that scientists now had a duty to go out and
communicate the benefits of science to a wider public, but also
that a more ‘scientifically literate’ public would be more
supportive of scientific research programs and more
enthusiastic about technological innovations. The results of
this survey shows that more than two-third of the farmers in
the counties surveyed were aware of GM crops, so it is
generally possible to engage them in the debate. However,
knowledge, sources of information, and attitudes varied by
level of education, gender and socioeconomic grouping.
However, there is significance between the independent and
the dependent variable according to the data analysis results.
Studies tracking public opinion should be conducted regularly,
in order to determine knowledge levels, capture the impact of
knowledge activities, and reveal trends. Studies should be
extended to the 47 counties in order to include these segments
of the population in the national discourse. The present study
provided some important insights to improve the methodology.
First, the different counties represent different types of
consumers. However, the number and respective percentage of
people that do farming activity in each county is not known.
Household surveys could solve this problem, and they are
therefore highly recommended. Further, future surveys can
move from open-ended to closed-ended questions.
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foods.
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food and agriculture 2003-2004.
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Contention:
vii. SPRINGER, A. et al (2002):Comparing Consumer Attitudes Towards
Genetically Modified Food in Europe. Mimeo.
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modified food.
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