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Record W2773895447 · doi:10.1521/soco.2017.35.6.663

The Making of Social Experience from the Sounds in Names

2017· article· en· W2773895447 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 · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicPsychology of Social Influence
Canadian institutionsUniversity of TorontoBaycrest HospitalThe Scarborough Hospital
Fundersnot available
KeywordsClosenessPsychologyMeaning (existential)Front (military)EmotionalityVowelSocial psychologyGazeLinguisticsSound (geography)CommunicationAcoustics

Abstract

fetched live from OpenAlex

People use names to infer meaning about the objects to which those names refer. Objects whose names include vowels produced toward the front of the mouth (Siri), relative to those with vowels produced toward the back of the mouth (Google), are expected to have certain physical features (e.g., smallness, sharpness, and quickness). Do these expectations map onto social experience? The present investigation examines this question through the lens of social closeness. Participants simulating an interaction with another person whose name included a front (versus a back) vowel sound saw that person as more socially connected to themselves (Study 1), which could facilitate the interaction (better tips for servers, Study 2) or undermine it (exacerbate negative emotionality, Study 3). Theoretical and practical implications note how the sounds in names not only create expectations but also sow the seeds for self-fulfilling prophecies to be borne out in experience.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.655
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0080.004
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.094
GPT teacher head0.444
Teacher spread0.350 · 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