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Record W2147046775 · doi:10.1177/0003122410368929

Stained Red

2010· article· en· W2147046775 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAmerican Sociological Review · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicCrime, Deviance, and Social Control
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsMoral panicHarmStigma (botany)Association (psychology)WrongdoingSpillover effectCriminologyPsychologyPolitical scienceSociologySocial psychologyLawPsychiatryEconomics

Abstract

fetched live from OpenAlex

We suggest that moral panics exert spillover effects through stigma by mere association. Individuals are harmed even if their ties to stigmatized affiliates are heterophilous, and high-status individuals can also suffer. This creates a broadcast effect that increases the scale of the moral panic. Analyzing the U.S. film industry from 1945 to 1960, we examine how artists’ employment in feature films was influenced by their associations with co-workers who were blacklisted as communists after working with the focal artist. Mere association reduces an artist’s chances of working again, and one exposure is enough to impair work prospects. Furthermore, actors’ careers are impaired when writers with whom they worked are blacklisted. Moreover, the negative effects of stigma by mere association hold even when the focal artist has received public acclaim. These findings have broad implications. When a few individuals or organizations are engaged in wrongdoing and publicly targeted, stigma by association can lead to false positives and harm many innocents.

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.

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)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.948
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.030
GPT teacher head0.398
Teacher spread0.367 · 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