Challenges in the remediation of compromised housing situations in individuals exhibiting hoarding behaviours
Bibliographic record
Abstract
Hoarding has been estimated to affect 2 to 5 percent of the population. There are considerable health and safety implications for those who hoard, others living with them, and for the community. For this reason, public health inspectors (PHIs) respond to situations involving vulnerable individuals living in these potentially adverse housing situations. Earlier research found that PHIs responding to these housing health hazards face many challenges in the remediation of these conditions including client health, structural factors, and policy issues. The purpose of this case study, approached from a social constructionist perspective, is to further explore the challenges in remediation of compromised housing health hazards in hoarding situations. The study included PHI’s documented reports of 40 cases referred to them between 2013 and 2015 as well as field observations and semi-structured interviews with an individual who hoards, his family, members of agencies involved with this case, and PHIs who respond to hoarding cases. This data is part of a larger two-year case study examining an Environmental Health Division’s response to housing health hazards in vulnerable populations. There were significant challenges in the remediation of hoarding. Client factors such as advancing age, infirmity, living alone, and lack of formal and informal supports hampered resolution of cases as did lack of training for PHIs about hoarding and its psychological ramifications. The lack of coordination of services within the City of Greater Sudbury, the magnitude of the cleanup required, and the chronic nature of hoarding also posed difficulties. The creation of a coalition to provide a more comprehensive response to hoarding is required to support this vulnerable population.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| 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".