The Most Cited Scholars in Five International Criminology Journals, 2006–10
Bibliographic record
Abstract
The current article examines three elements of scholarly influence comparing five major international criminology journals (BJC – British Journal of Criminology , CRIM – Criminology , ANZ – Australian and New Zealand Journal of Criminology , CJC – Canadian Journal of Criminology and Criminal Justice , EJC – European Journal of Criminology ) from 2006 to 2010. David Garland (BJC), Robert J. Sampson (CRIM and ANZ), Julian V. Roberts (CJC) and David P. Farrington (EJC) had the most overall influence, with Sampson the most cited over the five journals. Influence was both specialized, with some scholars having one or two highly cited seminal works, and versatile, with others having many different works cited several times each. The most cited works of the most cited authors were on developmental and life-course criminology and criminal careers.
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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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.047 | 0.060 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".