MétaCan
Menu
Back to cohort
Record W4399296680 · doi:10.1080/10511253.2024.2353656

“A Content Analysis of the American Society of Criminology’s Presidential Address, 1988–2022: A Qualitative Exploration”

2024· article· en· W4399296680 on OpenAlexafffund
Phillip Shon

Bibliographic record

VenueJournal of Criminal Justice Education · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsOntario Tech University
FundersUniversity of Ontario Institute of Technology
KeywordsContent analysisPresidential addressCriminologyCriminal justiceQualitative analysisPolitical sciencePresidential systemQualitative researchSociologyLawPublic administrationSocial science

Abstract

fetched live from OpenAlex

The number of articles published in peer-reviewed journals, publication in elite journals, inclusion in “classics” reading lists of graduate programs, and citation counts have been used as measures of scholarly influence. The annual addresses given by the presidents of the American Society of Criminology have escaped the attention of scholars in criminology and criminal justice as measures of scholarly influence. This shortcoming is notable for two reasons. First, the ASC presidents have often been included in previous indicators of scholarly influence. Second, the presidential addresses can be viewed as intellectual history of the discipline across time, delivered by influential scholars who have advanced criminology in meaningful ways. The current paper explores the ASC presidential addresses using qualitative methods. The findings indicate three key themes embedded in the addresses: (1) the public and private functions of criminology; (2) political feasibility of criminology; (3) crisis of legitimacy in criminology. The implications for criminology and criminal justice education are discussed.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.569

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.303
GPT teacher head0.495
Teacher spread0.192 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Criminal Justice EducationSame topicCrime Patterns and InterventionsFrench-language works237,207