Job Seekers’ Impression Management on Facebook: Scale Development, Antecedents, and Outcomes
Bibliographic record
Abstract
Many organizations rely on social media like Facebook as a screening or selection tool; however, research still largely lags behind practice. For instance, little is known about how individuals are strategically utilizing their Facebook profile while applying for jobs. This research examines job seekers’ impression management (IM) tactics on Facebook, personality traits associated with IM use, and associations between IM and job-search outcomes. Results from two complementary studies demonstrate that job seekers engage in three main Facebook IM tactics: defensive, assertive deceptive, and assertive honest IM. Job seekers lower in Honesty–Humility use more Facebook IM tactics, whereas those higher in Extraversion use more honest IM and those higher on Conscientiousness use less deceptive IM. Honest IM tactics used on Facebook are positively related to job-search outcomes. This paper therefore extends previous IM research by empirically examining IM use on Facebook, along with its antecedents and outcomes.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".