A grey literature review on media representation of animals in the 2023 wildfires in Nova Scotia, 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 study explores the media representation of animal-related issues during emergency response to wildfires in Nova Scotia, Canada. This paper aims to highlight the major issues present in the media during different stages of the emergency, looking specifically into three themes: preparedness, response, and recovery. The study adopts a content analysis approach to analyze data from multiple sources, including social media outlets (i.e., Twitter), government websites, and local news organizations’ publications between May and June 2023. The research highlights a range of practical examples when human-animal interactions can improve mutual resilience. To date, there are no unified standards for building media strategies related to supporting affected animals, specifically regarding the media representation of animal-related issues during disasters. The study offers a unique insight into the human-animal interactions during wildfires, a niche and specialised sub-field in disaster research.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it