Bibliographic record
Abstract
Although gender mainstreaming (GM) has been the international norm for working toward gender equality in policies and practices since theFourthWorldConference onWomen inBeijing 1995, its impact has been uneven. The lack of substantive results has led to debate surroundingGM'scapacity for engendering meaningful policy change. This article synthesizes the input of keyGMstakeholders (within government, academia, and nongovernmental organizations) acrossCanada,Australia,Sweden, theUnitedKingdom, andUkraine. It discusses national approaches to mainstreaming gender, identifies key factors inhibiting and/or promotingGM, and proposes how current strategies can be modified, strengthened and/or replaced by alternative approaches. Central to the analysis is the question as to whetherGMin current or expanded versions has the potential to addresses the wide variety of diversities among nation state populations. Related Media . 2013 . “.” http://www.eldis.org/go/topics/resource‐guides/gender/gender‐mainstreaming#.Ud7nzaz9zTo . 2012 . “.” Gender Equality. http://www.unesco.org/new/en/unesco/themes/gender‐equality/
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".