Bibliographic record
Abstract
B oth the content and authorship in this special edition provide us with a glimpse of a new era of Convict Criminology, what I refer to as Convict Criminology 3.0.In its infancy, Convict Criminology refl ected the exclusionary practices that are endemic in academia.This early era refl ects what I consider Convict Criminology 1.0 (1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008).Early membership was comprised largely of white men who had access to higher education, which refl ected academia's status as a predominately white male institution.While the informal Convict Criminology that emerged in the 1990s sought to amplify the voices and lived experiences of formerly incarcerated persons (Ross & Vianello, 2021), the membership did not refl ect the reality that incarceration disproportionately impacts lower-income individuals from communities of color.Moreover, the female voice was nearly nonexistent within the subfi eld's existing literature (Cox & Malkin, 2023).After 'the fi rst dime' (Jones et al., 2009), Convict Criminology expanded internationally and increased its presence within criminology, culminating in the establishment of a formal American Society of Criminology (ASC) division.I refer to this era as Convict Criminology 2.0 (2009 to 2019).The fi rst 25 years of Convict Criminology was an era of refl ection and growth.Today, Convict Criminology has entered a period of rebirth.This special edition marks a departure from the historical exclusivity that existed within the fi rst 25 years of Convict Criminology.While the narratives of men who served prison sentences dominated the fi rst 25 years, the next 25 years have the opportunity to provide a more intersectional and progressive view of life experiences within the criminal injustice system.Most notably, this special edition does not merely include one or two articles by women, the voices of system-impacted women dominate this edition.Moreover, the authors include people with direct experience and familial experiences with incarceration, which off ers a more complex view of the impact of the criminal injustice system.The articles in this special edition also off er a wide range of topics, provide both theoretical and empirical arguments and utilize both qualitative and quantitative methods.This special edition should be viewed as the fi rst step towards a Convict Criminology for the future.The progress refl ected in this special edition is indicative of larger shifts within Convict Criminology.The formal Division of Convict Criminology (DCC) is comprised of scholars from diverse backgrounds, experiences, genders, ages, and races.Our membership consists of individuals who
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How this classification was reachedexpand
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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".