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Record W3136200807 · doi:10.1521/soco.2021.39.2.295

The Effects of Online Status on Self-Other Processing as Revealed by Automatic Imitation

2021· article· en· W3136200807 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSocial Cognition · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsMcMaster University
Fundersnot available
KeywordsImitationPsychologyPriming (agriculture)Task (project management)Social statusCognitive psychologySocial cognitionSalientInformation processingSocial psychologyCognitionArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

High status individuals have been found to be less attuned to the behavior of others in the social environment. An important question is whether social status in an online setting affects social information processing in a way that resembles the known effects of real-world status on such processing. We examined differences in automatic imitation between Instagram “leaders” and “followers.” In Experiment 1, we found that followers exhibited more automatic imitation than leaders. Experiment 2 sought to establish whether this effect depended on status being salient, or whether it would occur spontaneously in the absence of priming. Results confirmed that thinking about status prior to the task is necessary for producing the pattern of effects in which high status individuals exhibit less automatic imitation than lower status individuals. We discuss our findings in relation to the effects of online status on self-other processing as assessed in the automatic imitation task.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.762
Threshold uncertainty score0.617

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.353
Teacher spread0.338 · 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