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Record W4312554474 · doi:10.33921/baof8361

The American Chill Pill : Tracking Demographic Changes in US Moral Rationalizations (1995-2020)

2022· article· en· W4312554474 on OpenAlexaffvenue
Hailey Pawsey, Kenneth M. Cramer

Bibliographic record

VenueJournal of Interpersonal Relations Intergroup Relations and Identity · 2022
Typearticle
Languageen
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsRationalization (economics)MoralityPsychologyDevelopmental psychologySocial psychologyDemographySociologyPolitical science

Abstract

fetched live from OpenAlex

Researchers have found that defense mechanisms are linked to moral reasoning. Age and sex are associated with defense utilization, wherein older individuals use mature defense mechanisms, and females use internalizing defenses. Research has identified that morality in society is declining. The present study evaluated the association of age, sex, and wave to rationalization in a situation involving moral reasoning. Age was hypothesized to correlate negatively with rationalizations, and females were hypothesized to utilize more rationalizations. Rationalization utilization was hypothesized to increase over time. Differences were found by age, suggesting older Americans were least likely to rationalize. Rationalization utilization increased over time among all ages. An interaction was found between age and wave, wherein the combination of variables predicted a participant’s mean rationalizations. This study fills a gap in the literature by examining how rationalizations change in a nation, helping to understand how society’s views on wrongdoings change with time.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.228

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.038
GPT teacher head0.292
Teacher spread0.254 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2022
Admission routes2
Has abstractyes

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