A developmental test of the general deviance syndrome with adjudicated girls and boys using hierarchical confirmatory factor analysis
Bibliographic record
Abstract
BACKGROUND: Over the last 40 years, numerous studies have proposed that various deviant behaviours are part of a latent construct now labelled 'general deviance' by criminologists or 'problem behaviour' by psychologists. During that period, many studies have documented the presence of specific forms of deviance. However, no study has tested these two opposing views simultaneously, particularly with longitudinal data. AIMS: The objectives of this paper are the cross-cultural replication of the construct of general deviance for a French-speaking adjudicated sample of girls and boys and, specifically, the developmental replication of the general deviance syndrome. METHOD: The age of onset is used as a developmental indicator of deviance instead of measures of participation or frequency. RESULTS: The results of EQS hierarchical confirmatory factor analyses supported the existence of the construct of general deviance. In addition, there is no gender gap in the structure of the general deviance syndrome. This paper reports a comprehensive test of the general deviance syndrome because of the use of 45 deviant behaviours and nine types of deviance classified into four categories.
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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 | 0.008 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".