Developing harm reduction policies: Evidence from Copenhagen's drug consumption rooms
Bibliographic record
Abstract
Ivan Christensen is the director of Mændenes Hjem. The remaining authors have no conflicts or potential conflicts to declare. Figure S1 Trends in average real estate price in Vesterbro and the rest of Copenhagen, 2010–2014. Figure shows the trends in average real estate prices (price per square metre) in Vesterbro, where Mændenes Hjem opened its permanent drug consumption room in the second quarter of 2012 (marked by the vertical dashed line), and the rest of the city of Copenhagen. Prices are indexed so prices in Vesterbro relative to the rest of Copenhagen are set to 100 in first quarter of 2012, just prior to the opening of the drug consumption room. Results are from authors' calculations using publicly available data from Finance Denmark (a business association for banks, mortgage institutions, asset management, securities trading, and investments funds in Denmark), which consist of the average actual sales prices per square metre of all traded real estate per quarter. Data retrieved on 2 December 2021, from https://rkr.statistikbank.dk/statbank5a/default.asp?w=3440 Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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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 | 0.027 | 0.120 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.001 |
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".