Physical health caregiver, mental wellness supporter, and overall well-being advocate: Women's roles towards animal welfare during the COVID-19 emergency response
Bibliographic record
Abstract
Women's health-specific contributions in emergency response stages pertain primarily to family and community-based rescue and support-focused roles. As disasters affect both human beings and their animal co-inhabitants, comprehensive literature exploring women's contributions towards companion animal welfare in emergency response settings remains sparse. COVID-19-triggered public health mitigation strategies caused diverse challenges relating to veterinary medical service access, thus establishing a platform for a nuanced exploration of gendered roles vis-a-vis animal health and well-being during the initial COVID-19 emergency response period. This project employs a semi-structured interview approach to qualitatively investigate the roles, responsibilities, and experiences of twelve people, eleven of whom self-identify as women, who cared for animal co-inhabitants while seeking veterinary medical services during the COVID-19 emergency response in Metro Vancouver, British Columbia, Canada. This research identifies three primary animal welfare-related roles that woman companion animal guardians (WCAGs) assumed during the COVID-19 emergency response period: 1) Companion animal physical health caregiver, spanning from nuclear to extended families and into the community; 2) Companion animal mental wellness supporter, associated with human-animal interactions in family/household, community, and veterinary clinic settings; 3) Companion animal holistic well-being advocate, utilizing various strategies at family, community, and societal levels. Understanding gender-specific animal welfare contributions in an emergency response setting narrows knowledge gaps and provides WCAGs and animal welfare-related public, private, and not-for-profit sectors with evidence-based strategies for emergency response planning improvements, supporting healthy and sustainable human-animal bonds in the current COVID-19 pandemic and future 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.
How this classification was reachedexpand
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 | 0.001 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".