IT Professionals’ Personality, Personal Characteristics, and Commitment: Evidence from a National Survey
Bibliographic record
Abstract
Drawing on personality traits theory (Costa & McCrae, 1985) and organizational commitment theory (Mowday, Steers & Porter, 1979), the purpose of the present study was to investigate, through four separate hierarchical regression procedures, the effect of a set of independent variables (neuroticism, gender, and generational age) on four separate dependent variables (DV): overall organizational commitment (OC), affective commitment (AC), continuance commitment (CC), and normative commitment (NC). The sample consisted of responses from 279 IT professionals in the United States, drawn from a national sample from the merged cross-sectional GSS 1972-2014 Cross-Sectional Cumulative Data, Release 5, March 24, 2016. Results of multiple regressions analyses revealed that, among IT professionals, neuroticism did not predict overall OC, AC, CC, or NC. Generational age predicted OC, AC, and CC with statistical significance. Gender predicted CC; none of the independent variables (IVs) predicted NC. Directions for future research are offered.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".