Homelessness quarterly progress report (April to June 2019)
Bibliographic record
Abstract
The annually agreed protocols between the Department and the nine regional lead authorities provide for submission of performance reports on a quarterly basis. These reports provide data in relation to exits to tenancies. In addition, the Department collates data on a monthly basis regarding the number of homeless persons accommodated in all forms of emergency accommodation funded and overseen by housing authorities. These reports are based on data provided by housing authorities and are produced through the Pathway Accommodation & Support System (PASS). The monthly reports outline the number of individuals accommodated in emergency accommodation over a designated survey week, including a breakdown by local authority. \nThe report below summarises the position at the end of Quarter 2 and takes account of both monthly statistics and quarterly performance reports submitted to the Department by local authorities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.061 | 0.023 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.011 | 0.003 |
| Bibliometrics | 0.026 | 0.034 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.023 | 0.013 |
| Research integrity | 0.005 | 0.016 |
| Insufficient payload (model declined to judge) | 0.003 | 0.065 |
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; both teacher heads agree on what is shown here.
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".