No pets allowed: A trans-species social justice perspective to address housing issues for older adults and companion animals
Bibliographic record
Abstract
INTRODUCTION: Significant benefits of companion animals (i.e., pets) for older adults are recognized and publications on Animal-Assisted Intervention, Animal-Assisted Activities and Animal-Assisted Therapies with older adults are growing. Studies on housing and community- residing older adults with companion animals from a non-utilitarian perspective on other animals, however, are rather limited.METHODS: For this scoping review, we used a Critical Animal Studies perspective, in particular, a trans-species social justice framework to address two questions: “What are the scope and size of the literature on housing for community living older adults with companion animals?” and “What is known from the existing literature?” We searched peer-reviewed publications from 1980 to 2019 by using MEDLINE, PsychINFO, ProQuest and Scopus.FINDINGS: Six works from Canada, Aotearoa New Zealand and US met our criteria. A disturbing reality was discovered: Restrictive leasing (‘no pets’ for rental housing) among low-income older adults with companion animals in public housing has persisted for the last 40 years and prevents them from accessing affordable housing. Also, the discourse of pets as problems or risk seems to justify prohibiting older adults from living with companion animals.CONCLUSION: Utilising the concept of speciesism and a trans-species social justice framework for analysis, we argue that intersectional institutional oppression of speciesism and classism is a root cause of the situation. Justice for older adults cannot be achieved without justice for their companion animals. Future studies in human–animal relations and education and practice in social work need to incorporate ideas of speciesism and justice beyond humans.
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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 | 0.026 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.008 | 0.036 |
| Scholarly communication | 0.010 | 0.015 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".