Revisiting the Measurement of Anomie
Bibliographic record
Abstract
Sociologists coined the term "anomie" to describe societies that are characterized by disintegration and deregulation. Extending beyond conceptualizations of anomie that conflate the measurements of anomie as 'a state of society' and as a 'state of mind', we disentangle these conceptualizations and develop an analysis and measure of this phenomenon focusing on anomie as a perception of the 'state of society'. We propose that anomie encompasses two dimensions: a perceived breakdown in social fabric (i.e., disintegration as lack of trust and erosion of moral standards) and a perceived breakdown in leadership (i.e., deregulation as lack of legitimacy and effectiveness of leadership). Across six studies we present evidence for the validity of the new measure, the Perception of Anomie Scale (PAS). Studies 1a and 1b provide evidence for the proposed factor structure and internal consistency of PAS. Studies 2a-c provide evidence of convergent and discriminant validity. Finally, assessing PAS in 28 countries, we show that PAS correlates with national indicators of societal functioning and that PAS predicts national identification and well-being (Studies 3a & 3b). The broader implications of the anomie construct for the study of group processes are discussed.
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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 | 0.013 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".