Gender-Based Experiences and Perceptions after the 2010 Winter Storms in Atlantic Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper conveys the findings of the first phase of a longitudinal study into climate change adaptation in Atlantic Canada. Men and women from 10 coastal communities in three provinces (Quebec, New Brunswick, and Prince Edward Island) were interviewed to better understand how both sexes perceived and reacted to extreme weather events. Their responses were recorded based on their experiences, personal and community levels of preparedness, as well as help received and effects on their lives. Most importantly, the findings denote that more men were personally prepared and more active in the community than women. More men recognized a deficiency in help at the community level, and were critical of government in particular, addressing a lack of financial interventions and support. Women were forthcoming with their emotions, admitting to feeling fear and worry, and their perceptions in terms of impacts and actions were closer to home. The results support what others have shown that in rural and coastal communities the traditional division of labor may influence and lead to a gender bias in terms of actions and gradual adaptation in communities. There is a need to better understand how these sometimes subtle differences may affect decisions that do not always consider women's roles and experiences in the face of extreme events.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it