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Record W2145800189 · doi:10.1007/s10806-012-9396-9

She Came, She Saw, She Sowed: Re-negotiating Gender-Responsive Priorities for Effective Development of Agricultural Biotechnology in Sub-Saharan Africa

2012· article· en· W2145800189 on OpenAlexfundno aff
Obidimma Ezezika, Jennifer Deadman, Abdallah S. Daar

Bibliographic record

VenueJournal of Agricultural and Environmental Ethics · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetically Modified Organisms Research
Canadian institutionsnot available
FundersUniversity of TorontoUniversity Health NetworkBill and Melinda Gates Foundation
KeywordsAgricultural biotechnologyAgricultureBiotechnologyFood securitySustainable developmentGender mainstreamingAgricultural communicationEconomic growthPolitical scienceBusinessGender equalityEconomicsSociologyBiologyLaw

Abstract

fetched live from OpenAlex

In this paper, we argue for the importance of incorporating a gendered perspective for the effective development of sustainable agricultural biotechnology systems in sub-Saharan Africa. Priority setting for agricultural policy and project development requires attention to gender issues specific to the demands of agricultural biotechnology. This is essential for successfully addressing food security and poverty reduction in sub-Saharan Africa (SSA). There has been a great deal of debate and literature on the implications of gender in agricultural development and policy. However, the implications of gender in agricultural biotechnology and have received relatively less attention, especially in SSA. Based on interviews with key stakeholders in agricultural biotechnology across SSA, review of pertinent literature and field observations, we have found that incorporating a gendered perspective is critical for the sustainable development of agricultural biotechnology and requires attention in five areas: the inclusion of women, particularly women farmers, in decision-making around biotech/genetically modified (GM) crop and trait selection; equal representation of women as men in education for agricultural science and in agricultural biotechnology research and development professions; greater involvement of women in extension services and farmers’ associations for successful delivery of information about biotech crops equality between men and women in access to resources for biotech/GM crop cultivation; and increased control for women farmers over biotech/GM crop management and income generation. We explain the consequences of failing to include such gender-responsive considerations into priority setting for agricultural biotechnology development and policy in SSA and provide recommendations for how policy makers and project partners of development initiatives can avoid such oversights.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.055
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.055
Threshold uncertainty score0.293

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0550.032
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0200.018
Scholarly communication0.0150.015
Open science0.0020.015
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.0060.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.045
GPT teacher head0.254
Teacher spread0.209 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations11
Published2012
Admission routes1
Has abstractyes

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