How well do hoarding research samples represent cases that rise to community attention?
Bibliographic record
Abstract
This study used archival data from three different research groups and case file data from three independent community organizations to explore how well research samples reflect cases of hoarding that come to community attention. Using data from 824 individuals with hoarding, we found that research volunteers differ from community clients in several ways: community clients are older, more likely to be male and less likely to be partnered; they have lower socio-economic status and are less likely to demonstrate good or fair insight regarding hoarding severity and consequences. The homes of community clients had greater clutter volume and were more likely to have problematic conditions in the home, including squalor and fire hazards or fire safety concerns. Clutter volume was a strong predictor of these conditions in the home, but demographic variables were not. Even after accounting for the influence of clutter volume, the homes of community-based clients were more likely to have squalor. These findings suggest limitations on the generalizability of research samples to hoarding as it is encountered by community agencies.
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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 | 0.036 | 0.164 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".