Core self‐evaluations, perceptions of group potency, and job performance: The moderating role of individualism and collectivism cultural profiles
Bibliographic record
Abstract
The current study examines the contingency role of individualism‐collectivism profiles on relationships involving core self‐evaluations ( CSE ), perceptions of group potency ( PGP ), and job performance. Theories of individualism and collectivism have thus far been mixed as to whether these are two distinct constructs or a single bipolar continuum, so latent profiles were considered as a novel perspective on this issue. A sample of 167 employees working in a Chinese vehicle manufacturing facility completed self‐report measures of all study variables except job performance, which was measured through supervisor ratings. Latent profile analyses revealed two profiles with either individualism or collectivism as dominant but not both. Further, CSE was a stronger predictor of job performance in employees with an individualism‐dominant cultural profile, whereas PGP was a stronger predictor of job performance in employees with a collectivism‐dominant cultural profile. As such, research investigating the main effects of CSE and PGP may overlook the qualifier of individualism‐ versus collectivism‐dominant cultural orientations. We offer theoretical and practical considerations regarding how employees experience individualism and collectivism simultaneously and how these experiences affect the interplay of predictor–criterion relations. Practitioner points Employees appear to experience one of two patterns or profiles of individualism or collectivism, such that the employee is relatively high on one construct and low on the other. Supervisors, trainers, and coaches need to consider profiles of individualism and collectivism, as the value of emphasizing core self‐evaluations versus perceptions of group potency to enhance job performance depends on the particular employee's dominance on either individualism or collectivism.
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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 | 0.002 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".