Global liberalization on homosexuality: Explaining the African gap
Bibliographic record
Abstract
We are trapped in two divergent worlds when it comes to global views on homosexuality. There is the liberal world epitomized by Spain and other nations, where homosexuality is increasingly accepted; gays and lesbians are claiming their human rights; and laws are changing to codify that transformation. The second is the extremely anti-gay world symbolized by Africa, the Middle East and parts of Asia, where attitudes are favorable to criminalization. This research explains the “African Gap” in attitudes toward homosexuality in a comparative analysis of six African nations and Argentina and Canada, South and North America's most liberal nations on gay rights. Using Pew's 2015 Spring Global Attitudes Survey data, we find that the major variables have essentially similar effects on opinion in any context. Africa's distinction is explained by its comparatively higher levels of factors such as religion, morality dogma, and low socioeconomic status that generally retard support for homosexuality, at the same time of lower levels of factors such as education, urbanization, and personal liberty that increase gay support. Africa's extreme anti-gay outlook is mutable. Two social forces will facilitate this softening: expansion of liberalizing agents such as education and urbanization, and repositioning away from “traditionalism” toward modernism emphasizing individualism, civil rights, and personal liberties.
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 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".