One Health, the Human-Animal Bond and Well-Being During the Covid 19 Pandemic
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
Using a One Health lens, this study explored whether the strength of the bond between humans and non-human animals would predict well-being during the COVID-19 pandemic. Based on the substantial existing research done over the last several decades, we hypothesized that the presence of non-human animals (NHAs) may be linked directionally to well-being. Participants were recruited to this online survey using social media. A demographic survey as well as the World Health Organizations’ Well-being Scale (WHO5) and 10-item Pet Attachment Scale (PAS) were used. Results showed that the human-animal bond, as measured by the 10-item PAS, was the only significant predictor of well-being. The bond with NHAs itself was influenced by the role non-human animals play, with the strongest bond among those who reported that they considered NHAs to be family members. The article concludes that preserving and supporting the human-animal bond during stressful and dangerous times, such as a pandemic, is an important mental and physical health protective strategy that governments should support.
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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 | 0.003 | 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 it