Systematic review of psychosocial factors associated with evictions
Bibliographic record
Abstract
Evictions from rented accommodations are a common pathway to homelessness and can negatively impact the lives of individuals and communities worldwide. There have been only few interventions developed to address evictions, and it is important to first understand factors associated with evictions. This systematic review included all available peer-reviewed articles on the topic published in the international literature from 1900 to 2017 and identified 10 peer-reviewed studies of evictions conducted in the United States, Canada, Amsterdam and Britain. From these studies, four categories of factors associated with evictions were identified. These factors were financial hardships, sociodemographic characteristics, substance use and other health problems. While many studies had large sample sizes, the majority of studies were cross-sectional. Together, our review found that there were several salient factors known to be associated with evictions which may benefit from intervention. However, more prospective studies on evictions and development of interventions are needed.
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How this classification was reachedexpand
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 | 0.011 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.006 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.005 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".