Ingratiation in job applications: impact on selection decisions
Bibliographic record
Abstract
Purpose The purpose of present study is to examine the influence of impression management (IM) tactics (e.g. ingratiation) applied in job application letters on perceived qualifications and hiring recommendations. The study aims to build on recent research done in the interview context, by studying IM specifically in the written form pertaining to a job application. Design/methodology/approach Data were gathered from 94 respondents asked to evaluate the job application letters of applicants for a mentoring program. IM was manipulated through the cover letter, such that, each subject received five cover letters, four of which engaged in ingratiation and one that had no ingratiation. Participants were required to evaluate the applicants' qualifications and make selection decisions. Findings The results of the study were consistent with those of the interview context. More specifically, ingratiation led to significantly higher ratings of applicants, and self‐focused tactics were more effective than other‐focused tactics. Research limitations/implications The findings of this research conveyed that most of the IM tactics significantly improve recruiters' evaluations of the applicants. Still, future research needs to further investigate this relationship in order to understand the specific nature of the IM tactics and develop a deeper understanding of the underlying processes that cause IM tactics to have an impact on recruiters' judgments. Practical implications The present study highlights the need for greater understanding of how IM tactics may influence the decisions of employers who rely on written applications, or a combination of job application letters and interviews. Therefore, employers need to be aware of the use of IM in written applications and emphasize the importance of interviews in the selection process. Originality/value Existing research has been concerned with how IM tactics influence interview outcomes and has overlooked how these same IM tactics may be used in job application letters to influence selection decisions. This study addresses this gap by focusing on the job application letter as a means of conveying and managing impressions by candidates.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".