How is adaptation, resilience, and vulnerability research engaging with gender?
Bibliographic record
Abstract
The gendered dimensions of climate change have received increasing interest in climate change adaptation, resilience, and vulnerability (ARV) research. Yet concerns have been expressed that engagement with 'gender' in this work has been tokenistic. In this context, we ask: how is climate change ARV research engaging with gender? To answer this question, we develop an assessment framework capturing key attributes of engagement and use it to evaluate peer reviewed ARV articles with a focus on gender published since 2006 ( n = 123). Results indicate an increase in ARV studies with a gender focus over this period, with the level of gender engagement also increasing. There are a relatively equal numbers of studies categorized as engaging gender at a high, medium, and low level, with studies from Sub-Saharan Africa consistently exhibiting high levels of gender engagement. Gender focused ARV has a strong focus on examining female experiences, with few studies explicitly focusing on men, and no work accounting for those identifying outside the gender binary.
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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 | 0.076 | 0.100 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.017 | 0.023 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".