L’analyse stratégique et quelques développements récents en criminologie
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Strategic analysis views crime as a confrontation and as a mean to an end. It is characterised by : 1) it concentrates on crime; 2) it takes cognizance of the circumstances under which the crime is committed; 3) it presents the crime as a decision influenced by its anticipated results. Felson's routine activity approach, which is similar to strategic analysis, is presented in this article. Other recent developments in criminology have made it possible to present several assertions with a view to explaining certain aspects of theft, in particular, the choice of target. These assertions are : 1) thefts vary according to the opportunities offered potential thieves; 2) opportunity is defined as the contact between a potential criminal and a suitable target; 3) the number of contacts between potential criminals and suitable targets varies directly with the number of targets and their accessibility; 4) the suitability of targets varies in direct proportion to their value and vulnerability. It varies in inverse proportion to their inertia.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it