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Record W4200309846 · doi:10.1177/19485506211063259

Should I Ask Over Zoom, Phone, Email, or In-Person? Communication Channel and Predicted Versus Actual Compliance

2021· article· en· W4200309846 on OpenAlexaff
Mahdi Roghanizad, Vanessa K. Bohns

Bibliographic record

VenueSocial Psychological and Personality Science · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicPsychology of Social Influence
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsVignetteSeekersPsychologyPhoneAsk priceSocial psychologyInternet privacyZoomChannel (broadcasting)Applied psychologyComputer science

Abstract

fetched live from OpenAlex

Research has found that people are much more likely to agree to help requests made in-person than those made via text-based media, but that help-seekers underestimate the relative advantage of asking for help face-to-face. It remains unknown what help-seekers’ intuitions about the effectiveness of richer media channels incorporating audio and video features might be, or how these intuitions would compare with the actual effectiveness of face-to-face or email versus rich media requests. In two behavioral and two supplemental vignette experiments, participants expected differences in the effectiveness of seeking help through various communication channels to be quite small, or nonexistent. However, when participants actually made requests, the differences were substantial. Ultimately, help-seekers underestimated the relative advantage of asking for help face-to-face compared with asking through any mediated channel. Help-seekers also underestimated the relative advantage of asking through richer media channels compared with email.

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 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)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.752
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.009
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.350
GPT teacher head0.478
Teacher spread0.128 · 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; both teacher heads agree on what is shown here.

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

Citations14
Published2021
Admission routes1
Has abstractyes

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