Tracing the Criminal: The Rise of Scientific Criminology in Britain, 1860-1918
Bibliographic record
Abstract
Tracing the Criminal provides a remarkable account of the reception of scientific criminology in Britain during the period 1860–1918. Neither universally embraced, nor uniformly rejected, scientific criminology argued that the criminal constitute a sub-human category that was distinguishable from ‘normal’ law-abiding members of society. Examining the ideas and research of the era, Neil Davie elucidates the reception of this claim in British criminology, representing a radical shift in thinking about ‘the criminal’ that went beyond a taxonomic capacity to an ability to provide ‘scientific’ explanations of criminals and criminality. This latter claim reflects a positivistic belief that—through scientific methods and evidence—it was possible to ‘know’ the criminal. The Foreword, written by Bryan S. Turner, crystallizes the implications of the Lombrosian ‘born criminal type’ and links the substantive focus of Tracing the Criminal to contemporary debates. In the Introduction, Davie notes that Darwinian thought posed a threat to professional British criminologists, who were primarily employed by the state in the Prison Service. The idea that the ‘criminal’ and/or ‘criminality’ was inherent in specific individuals rendered the criminologist a glorified ‘gaoler’ of those incarcerated for their nature. This idea carried with it a sense of fatalism: once a person exhibited criminal tendencies, little could be done other than incarceration. Ironically, criminologists leveraged this fatalism to argue for a criminological agenda that focused on prisons and deterrence. During the last decades of the nineteenth century, the prison, through mediatization, served as a site for professionalization. Medical personnel were not content to simply assess prisoners for administrative purposes, and sought a more ‘rewarding and socially prestigious function’ than that of a ‘filing clerk’.
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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 | 0.014 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.011 | 0.050 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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".