GENDER UNDER "DEVELOPMENT": A STUDY OF CONDITIONS FOR WOMEN IN FOUR COUNTRIES by
Bibliographic record
Abstract
This multi-site, mixed-methods study of the ways in which gender is conceived and practiced across 'developed' and 'developing' nations offers a critical inquiry into the varied impacts and experiences of 'development' on women.From a post-structural perspective, this study critically examined key discourses culturally available in Western scholarly and popular publications (including online news articles and NGO donor information) concerning relationships between 'development' and cross-national conditions for women, and the realities and subjectivities they produced.The conceptual and analytical diversity evidenced in the scholarly literatures was not found in the popular media reviewed; rather, these publications presumed and presented hierarchical assumptions of Western superiority over other less 'developed' regions with respect to conditions for women.To extend and deepen the analysis of both academic and popular literature, 'fictional' representations in the form of cartoon constructions, as well as 'factual' selfreports of gender-equity and development, were solicited from participants in four countries (Sri Lanka, Canada, Botswana, and Norway).These accounts were then mapped on to institutional policies and practices in order to understand how they impinged upon the lives of differently positioned women.At a national level, relationships between 'development' and conditions for women proved to be extremely complex.Factors that enabled advancement for (some) women differed from one country to the next, for instance legal rights and social assistance in Canada and Norway, free education in Sri Lanka, and the availability of affordable domestic labour in Botswana.Factors that constrained or impeded gender-equity, too, differed across national contexts, iv however they often produced comparably inequitable results.For example, women in Canada appeared to be more regulated indirectly by state structures than regulated directly within the domestic sphere, making sexism less visible and, precisely for that reason, harder to identify and thus harder to combat than in countries where direct and overt gender discrimination is prevalent.At a local level, women's ethnicity, class, familial status, age, education, and occupation intersected in different ways to produce quite different lived experiences even within the same national context.These findings trouble associations between the advancement of conditions for women and national 'development.'
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.016 | 0.011 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".