MétaCan
Menu
Back to cohort
Record W2080645735 · doi:10.1037/0021-9010.88.5.944

Applicant reactions to face-to-face and technology-mediated interviews: A field investigation.

2003· article· en· W2080645735 on OpenAlex
Derek S. Chapman, Krista L. Uggerslev, Jane Webster

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 Applied Psychology · 2003
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEmployer Branding and e-HRM
Canadian institutionsQueen's UniversityUniversity of Calgary
Fundersnot available
KeywordsPsychologyVideoconferencingFace-to-faceSocial psychologyPerceptionTelephone interviewComputer-mediated communicationApplied psychologyMultimediaThe InternetSociologyComputer science

Abstract

fetched live from OpenAlex

This field study examined applicant reactions (N = 802) toward face-to-face as compared with technology-mediated interviews (through videoconferencing or by telephone) for 346 organizations. Face-to-face interviews were perceived as more fair and led to higher job acceptance intentions than were videoconferencing and telephone interviews. Perceived interview outcomes were higher with face-to-face and telephone interviews over videoconferencing. Self-monitoring moderated the relationship between interview medium and perceptions of fairness. Specifically, this relationship was (a). positive for face-to-face, (b). negative for telephone, and (c). nonsignificant for videoconferencing interviews. Moreover, the number of offers an applicant received moderated the relationship between interview medium over, and perceived fairness. The relationship between number of offers and perceived fairness was positive for face-to-face and negative for technology-mediated interviews.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.376
Threshold uncertainty score0.516

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
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 head0.027
GPT teacher head0.283
Teacher spread0.256 · 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