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Record W2241564634 · doi:10.4324/9781315178103-10

The Influence of Behavior on Attitudes

2005· article· en· W2241564634 on OpenAlexaff
James M. Olson, Jeff Stone

Bibliographic record

VenueDialnet (Universidad de la Rioja) · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsWestern University
Fundersnot available
KeywordsCounterintuitiveRelation (database)Social psychologyPsychologyEpistemologyCognitive psychologyComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

In most laypersons’ implicit theories of the causes of everyday events, attitudes influence behavior: People’s actions are guided by their internal attitudes. Although social psychologists have certainly investigated this relation (as illustrated most directly by the work described in the preceding chapter), they have given just as much attention to the reverse relation: the influence of behavior on attitudes. This topic has stimulated some of the best known and most-tested theories in social psychology and has elicited significant public interest because it turns laypersons’ implicit theories upside down and generates counterintuitive predictions (which have been confirmed). Our goal in this chapter is to review and evaluate this research literature.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.761
Threshold uncertainty score0.355

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.015
GPT teacher head0.328
Teacher spread0.313 · 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 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

Citations100
Published2005
Admission routes1
Has abstractyes

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