Conceptualizing Homeless Exits and Returns: The Case for a Multidimensional Response to Episodic Homelessness
Bibliographic record
Abstract
Research indicates that homelessness is dynamic and that a significant number of homeless people have experienced multiple episodes of homelessness. This episodic nature of homelessness implies that the issue for such people is not only getting housing and exiting homelessness but staying housed or when there is a need to move, making a transition to another housing without returning to homelessness. This article describes a multidimensional conceptual model that was developed by synthesizing the theoretical and research literature on homelessness. Essentially, this model identifies four dimensions in society within which multi-layered factors that impact on housing outcomes are located. The multidimensional model underscores the fact that exits and returns to homelessness are determined by a complex interaction of individual and structural factors necessitating a multilevel and integrated response to episodic homelessness.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.030 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.006 |
| 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".