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Record W4396821038 · doi:10.1515/mc-2023-0062

The salience of students’ body language during in-person and online lectures at a Canadian university

2024· article· en· W4396821038 on OpenAlexaffabout
Giuliana Salvato

Bibliographic record

VenueMultimodal Communication · 2024
Typearticle
Languageen
FieldPsychology
TopicCommunication in Education and Healthcare
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsSalience (neuroscience)PsychologyMathematics educationCognitive psychology

Abstract

fetched live from OpenAlex

Abstract Professors teaching different disciplines at a university in Canada received an email invitation to fill-out an online questionnaire where they could reflect on and express their opinions about the pedagogical and communicative roles of the body during their lectures. The questionnaire was divided into two parts: one asking professors to comment on their own body language; the other inquiring about professors’ perception of their students’ body language usage. This article is specifically focused on the second part of the survey, where professors reacted to questions concerning awareness of students’ body language during classes held in-person and online. In investigating the perceived salient functions attributed to students’ body language, this study values multimodal competence, embodied communication, and it informs the concept of immediacy in the relationship between students and professors at the university level.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.203
Threshold uncertainty score0.404

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.002
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.025
GPT teacher head0.374
Teacher spread0.349 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2024
Admission routes2
Has abstractyes

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