Companion-Animal Relinquishment: Exploration of the Views Expressed by Primary Stakeholders within Published Reviews and Commentaries
Bibliographic record
Abstract
Abstract There is a need to further understand companion-animal relinquishment in order to prevent it. This study explored published reviews and commentaries, written by primary stakeholders, on companion-animal relinquishment, including 77 reviews and commentaries published between 1973 and 2011. The analysis-method framework is conducive to analyzing reviews and commentaries on a complex social phenomenon such as companion-animal relinquishment. Four themes emerged: identified reasons caretakers relinquish, solutions to relinquishment, euthanasia as an outcome of relinquishment, and the role of research in addressing relinquishment. Research-based views about reasons for relinquishment were most commonly discussed. Only a few research articles were cited, highlighting the impact of these few studies on stakeholders’ perceptions. The predominant solution discussed was education, while future research suggestions focused on investigating interventions. Findings provide insight into the influences on stakeholders’ views, including their use and interpretation of existing 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.
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 | 0.302 | 0.609 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.022 | 0.019 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".