Whose criminology? : marginalised perspectives and populations within student production at the Montreal School of Criminology
Bibliographic record
Abstract
This study assumes that criminological student production reflects departmental and disciplinary tendencies. We empirically investigate the prevalence of and relationship between marginalised populations and criminological perspectives based on two decades’ worth of thesis and dissertation abstracts published by the Montreal School of Criminology in Québec, Canada (µ=408). Descriptive statistics show the overwhelming prevalence of conventional criminology (72%) compared to studies questioning or discussing alternatives to the status quo. A minority of studies consider marginalised populations. We then examine factors predicting non-conventional perspectives within student production, using a logistic regression model. Studies considering race, social class, sociological aspects within criminology, or resorting to qualitative methods show the strongest likelihood of relying on non-conventional perspectives, whereas studies considering age increase the likelihood of relying on conventional perspectives. In closing we urge criminologists working within all perspectives to meaningfully include and consider how their work impacts marginalised populations.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".