Social Networking Sites and Personnel Selection: An Initial Validity Assessment
Bibliographic record
Abstract
The purpose of this dissertation was to add to the literature on the use of social networking sites (SNSs) for personnel selection. The first goal was to evaluate whether SNSs have the potential to be used as a valid source of information for selection. Specific SNS Indicator scales were created to test whether they have better validity evidence than the more traditionally-used Global SNS Rating. In a study of 141 undergraduate students at a large Canadian university, the Specific SNS Indicators demonstrated fairly weak evidence of interrater reliability, but some evidence of structural validity, and construct validity (convergent and discriminant). Specific SNS Indicator scales offered incremental prediction beyond a Global SNS Rating in the prediction of their traditional selection scales. This supported previous research suggesting that making info-processing easier for raters should lead to better validity (Heneman, 1986). The second goal was to investigate some of the practical realities of attaining SNS information. In a study of 892 employed or previously-employed participants, participants were given a hypothetical employer request for their SNS password as part of a job application. The study found that 57.87% applicants would refuse the request, and would thus remove themselves from the applicant pool. This substantial loss of applicants could lower the utility of an organizations selection system and thereby impact an organization’s bottom line. Also, the password request could result in adverse impact for protected groups, and lead to legal action on behalf of applicants within these groups. There was only a slight potential benefit to the loss of applicants in that those remaining in the pool were slightly higher on Agreeableness and Conscientiousness, and lower on Psychopathy. However, the effect sizes were small, and those remaining in the applicant pool scored higher on Impression Management, suggesting that their more favorable personality scores may have been dissimulated. I recommend that hiring managers refrain from using SNSs for selection until more validation research can be conducted on SNS information.
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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 | 0.061 | 0.089 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".