The spatial stability of alcohol outlets and crime in post‐disaster Christchurch, New Zealand
Bibliographic record
Abstract
The devastating Canterbury Earthquakes of 2010 and 2011 left an indelible mark on the city of Christchurch. The social and economic upheaval that immediately followed the Earthquakes has, in time, been replaced with a period of rebuild and transformation. In this study we investigate the effects that the Canterbury Earthquakes had on two important and inter‐related phenomena in the city: alcohol availability and crime. More specifically, we investigate how alcohol outlets and crime across six different categories changed in magnitude and spatial distribution pre‐ (end‐2009) and post‐ (end‐2014) earthquake. We do this using a variety of geospatial techniques including a relatively new method: the spatial point pattern test which allows for the identification of changes in spatial patterns at the local level. Results indicate that both alcohol outlets and crime have decreased in magnitude since the Canterbury Earthquakes. Using the spatial point pattern test we found statistically significant differences in spatial point patterns for both alcohol outlets and all crime types pre‐ to post‐earthquake. The similarity in the differences of the spatial distributions of alcohol outlets and crime provides a first empirical clue of their potential association in the city post‐earthquake.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".