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Record W2121719018 · doi:10.1177/009365001028003004

Impression Formation in Computer-Mediated Communication Revisited

2001· article· en· W2121719018 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

VenueCommunication Research · 2001
Typearticle
Languageen
FieldPsychology
TopicTeam Dynamics and Performance
Canadian institutionsDalhousie University
Fundersnot available
KeywordsImpression formationPsychologyConversationImpressionNeuroticismPersonalitySocial psychologyContext (archaeology)AttributionImpression managementBig Five personality traitsFace (sociological concept)Computer-mediated communicationCognitionTraitConscientiousnessExtraversion and introversionPrecedentCognitive psychologySocial perceptionComputer sciencePerceptionLinguisticsCommunication

Abstract

fetched live from OpenAlex

Following either a text-based, synchronous computer-mediated conversation (CMC) or a face-to-face dyadic interaction, 80 participants rated their partners' personality profile. Impressions were assessed in terms of both their breadth (the comprehensiveness of the impression) and intensity (the magnitude of the attributions). Results indicated that impressions formed in the CMC environment were less detailed but more intense than those formed face-to-face. These data provide support for theories that, in addition to acknowledging the unique constraints and characteristics of CMC, consider the cognitive strategies and heuristics involved in the impression formation process. The differential impact of a text-based medium on trait-specific impressions (e.g., extraversion, neuroticism) is also discussed in the context of a cross-modal approach to impression formation.

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)0.003
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.791
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.124
GPT teacher head0.458
Teacher spread0.334 · 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