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Biases in Interpersonal Communication: How Engineering Students Perceive Gender Typical Speech Acts in Teamwork

2009· article· en· W2008357511 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

VenueJournal of Engineering Education · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsECW Press (Canada)
Fundersnot available
KeywordsTeamworkInterpersonal communicationPsychologyPerceptionStrengths and weaknessesSocial psychologyFace (sociological concept)Applied psychologySpeech communicationLinguisticsPolitical science

Abstract

fetched live from OpenAlex

Abstract This research investigates differences in how engineering and non‐engineering men and women perceive common speech acts in team settings. Participants completed surveys asking them to rate the speakers of three male typical and three female typical speech acts. Male engineering students were significantly harsher than other groups on female typical speech acts in which the speaker conceded weaknesses, even if this concession was for strategic purposes such as trying to help another teammate “save face.” This bias against female typical speech was consistent regardless of the speaker's gender, suggesting that students were reacting to speech patterns rather than to biological gender. These findings provide hope that women may be able to help manage perceptions of their everyday team interactions by avoiding statements that imply weaknesses, even if such speech is normal in other situations.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.540
Threshold uncertainty score0.324

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 studies0.0000.000
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 head0.035
GPT teacher head0.370
Teacher spread0.335 · 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