MétaCan
Menu
Back to cohort
Record W4311331323 · doi:10.1080/1359432x.2022.2156862

Is more always better? How preparation time and re-recording opportunities impact fairness, anxiety, impression management, and performance in asynchronous video interviews

2022· article· en· W4311331323 on OpenAlexafffund
Nicolas Roulin, Odelia Wong, Markus Langer, Joshua S. Bourdage

Bibliographic record

VenueEuropean Journal of Work and Organizational Psychology · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEmployer Branding and e-HRM
Canadian institutionsUniversity of CalgarySaint Mary's University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsImpression managementPsychologyAnxietyAsynchronous communicationAffect (linguistics)Applied psychologySocial psychologyImpression formationSample (material)PerceptionComputer scienceSocial perception

Abstract

fetched live from OpenAlex

The present study examined how variations in the design of asynchronous video interviews (AVIs) impact important interviewee attitudes, behaviours, and outcomes, including perceived fairness, anxiety, impression management, and interview performance. Using a 2 × 2 experimental design, we investigated the impact of two common and important design elements on these outcomes: (a) preparation time (unlimited versus limited) and (b) the ability to re-record responses. Using a sample of 175 participants completing a mock AVI, we found that whereas providing such options (i.e., unlimited preparation time and/or re-recording) did not impact outcomes directly, the extent to which participants actually used these options did affect outcomes. For instance, those who used more re-recording attempts performed better in the interview and engaged in less deceptive impression management. Moreover, those who used more preparation time performed better in the interview while engaging in slightly less honest impression management. These findings point to the importance of investigating the effects of AVI design on applicant experiences and outcomes. Specifically, AVI design elements produce opportunities for applicants not typically present in synchronous interviews, and can alter interview processes in crucial ways. Finally, not all applicants use these opportunities equally, and this has implications for understanding interview behaviour and outcomes.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.511

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.030
GPT teacher head0.262
Teacher spread0.232 · 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 teacher head, 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

Citations29
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueEuropean Journal of Work and Organizational PsychologySame topicEmployer Branding and e-HRMFrench-language works237,207