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Record W4389037769 · doi:10.1111/ijsa.12460

Exploring the role of interviewee cognitive capacities on impression management in face‐to‐face and virtual interviews

2023· article· en· W4389037769 on OpenAlexafffund
Benjamin Moon, Stephanie Law, Joshua S. Bourdage, Nicolas Roulin, Klaus G. Melchers

Bibliographic record

VenueInternational Journal of Selection and Assessment · 2023
Typearticle
Languageen
FieldPsychology
TopicDeception detection and forensic psychology
Canadian institutionsSaint Mary's UniversityUniversity of Calgary
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyCognitionImpression formationImpression managementPersonalityFace (sociological concept)Social psychologyBig Five personality traitsJob interviewApplied psychologyPerceptionSocial perception

Abstract

fetched live from OpenAlex

Abstract Interviewees' use of impression management (IM) in job interviews is clearly related to individual differences such as personality. However, research has paid less attention to how interviewee cognitive capacities (i.e., cognitive ability and executive functions) influence IM use, even though interviewees’ cognitive capacities and IM are theoretically linked. The current research aimed to address this research gap through two studies. In Study 1, 166 undergraduate business students participated in mock face‐to‐face interviews with real recruiters. In Study 2, 294 job‐seeking participants recruited through Prolific completed a mock asynchronous video interview. Overall, cognitive ability was negatively related to deceptive IM while perceived incongruency (i.e., a gap between desired and perceived current impressions conveyed to others) was positively related to deceptive IM in both studies. Furthermore, cognitive ability and working memory updating, but not inhibition and shifting nor incongruency, were negatively related to honest IM in Study 2. Additionally, in both studies the relations between personality traits and interview IM were generally in line with findings from prior research. Overall, our findings provide a more comprehensive understanding of how interview IM relates to interviewee individual differences and interview performance in different forms of job 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.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.974
Threshold uncertainty score0.282

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.097
GPT teacher head0.404
Teacher spread0.307 · 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 designOther design
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

Citations4
Published2023
Admission routes2
Has abstractyes

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