Tracing Gender Equality Cultures: Elite Perceptions of Gender Equality in Norway and Sweden
Bibliographic record
Abstract
Cultural explanations are frequent in social science research. In gender studies, they are especially common in cross-country comparative research that attempts to explain variations in everyday life situations for women and men. A noticeable example is found in the book Rising Tide: Gender Equality and Cultural Change Around the World, by Ronald Inglehart and Pippa Norris (2003). Inglehart and Norris construct a gender-equality scale from measurements on attitudes among citizens regarding women as political leaders, women's professional and educational rights, and women's traditional role as mother. The results show that Finland, Sweden, West Germany, Canada, and Norway are the countries most influenced by egalitarian values. At the other end of the spectrum countries like Nigeria, Morocco, Egypt, Bangladesh, and Jordan are found (p. 33). The authors demonstrate that egalitarian values are systematically related to the actual conditions of women's and men's lives. They conclude that modernization underpins cultural change, that is, attitudinal change from traditional to gender-equal values, and that these cultural changes have major impact on gender-equality processes.
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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| 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".