Measuring Collective Action Intention Toward Gender Equality Across Cultures
Bibliographic record
Abstract
Abstract: Collective action is a powerful tool for social change and is fundamental to women and girls’ empowerment on a societal level. Collective action towards gender equality could be understood as intentional and conscious civic behaviors focused on social transformation, questioning power relations, and promoting gender equality through collective efforts. Various instruments to measure collective action intentions have been developed, but to our knowledge none of the published measures were subject to invariance testing. We introduce the gender equality collective action intention (GECAI) scale and examine its psychometric isomorphism and measurement invariance, using data from 60 countries ( N = 31,686). Our findings indicate that partial scalar measurement invariance of the GECAI scale permits conditional comparisons of latent mean GECAI scores across countries. Moreover, this metric psychometric isomorphism of the GECAI means we can interpret scores at the country-level (i.e., as a group attribute) conceptually similar to individual attributes. Therefore, our findings add to the growing body of literature on gender based collective action by introducing a methodologically sound tool to measure collective action intentions towards gender equality across cultures.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".