Gender and the human dimensions of climate change: global discourse and local perspectives from the Canadian Arctic
Bibliographic record
Abstract
Climate change impacts will be mediated by gender. This thesis examines climate change and gender at both a global and local scale. Globally, as recognition of the role gender plays in one's climate change experience grows, so too does concern that engagement with concepts of gender has been tokenistic. In response, this thesis begins by examining to what extent climate change adaptation, vulnerability and resilience literature engages with concepts of gender, by developing an assessment framework. This systematic literature review finds that while high, medium, and low levels of engagement are relatively equal, there is great disparity in the literature in terms of both geographic regions of focus and genders of focus. In response to a gap in research on climate and gender from a North American context, this thesis develops local case study, identifying and examining the vulnerability and adaptive capacity of Inuit women in Iqaluit, Nunavut. Interviews were conducted with 42 Inuit women, and were complimented with focus groups, participant observation, and photovoice, to examine how women have experienced and responded to changes in climate already observed. Three key traditional activities were identified as being exposed and sensitive to changing conditions: berry picking, sewing, and the amount of time spent on the land. Key determinants of adaptive capacity included: mental health, physical health, traditional/western education, access to both country food and store bought foods, access to financial resources, social networks and connection to Inuit identity. This thesis finds that gender roles result in different pathways through which changing climatic conditions affect people locally, although the broad determinants of vulnerability and adaptive capacity for women are consistent with those identified in the scholarship more broadly for men.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.056 | 0.021 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".