Bibliographic record
Abstract
Housing First has gone global. In 2010, FEANTSA, the European Federation of Homelessness Organisations, organised a major pan-European 'consensus conference' in Brussels that recommended European use of housing-led and Housing First services. The 2013 annual European Observatory on Homelessness Conference in Berlin was called 'Housing First, What's Second? ' At every annual conference since then, paper after paper has been about the results of Housing First pilots, projects and programs in different European countries.3 The English Federation of Homelessness Organisations, Homeless Link, has built a network, Housing First England while Fio. PSD, the Italian Federation of Homelessness Organisations created Housing First Italia, both these national networks share ideas and advocate the use of Housing First. The Danish, Finnish and Norwegian homelessness strategies all use Housing First, while Lund University has been promoting Housing First in Sweden. Housing First services have been running in the Netherlands and the United Kingdom (UK) for years. A Canadian pilot program, 'At Home/ Chez Soi', and a French pilot 'Un chez soi d'abord', both led to national Housing First programs. England began experimenting with Housing First at national level this year.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.386 | 0.100 |
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".