Towards Gender Equality a Comparative Analysis of Gender Attitudes in Africa
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Gender attitudes and its factors continue to be debated in an era where gender equality remains a priority to countries in the world. Modernization theorists have assumed a predictable positive pattern of the influence of economic development on gender attitudes, thereby arguing that higher levels of economic development such as GDP per Capita, increases support for gender equality across countries. Whereas this has been proven in European and Western countries, it is difficult to generalize the results to African countries as the phenomenon is understudied on the continent. Using data from the 5th round of the Afrobarometer survey and multiple regression/multi-level analysis, this study investigated the influence of economic development, in addition to other socio-cultural factors, on gender attitudes in 34 African countries. The study revealed that a) among countries in Africa, economic development, in this case GDP per Capita, does not significantly influence attitudes towards gender equality; b) people’s ethnic background influences their attitudes towards gender equality; and c) Gender attitudes are strongly influenced by education, employment status and religious denomination.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it