Relationship between occupational commitment and ascribed importance of organisational characteristics
Bibliographic record
Abstract
Purpose This purpose of this paper is to investigate the relationship between dimensions of commitment to the profession of business, and ascribed importance of various organisational characteristics to the first full‐time job following graduation. Design/methodology/approach Business administration students (n=446) completed surveys on dimensions of their commitment to the profession of business and the importance they ascribed to having certain organisational characteristics in their first full‐time job (n=132). Confirmatory factor analysis of commitment scales, principal component analysis of organisational characteristics, and canonical correlations were used. Findings Affective occupational commitment was differentially, positively associated with the importance ascribed to working in an organisation that offers opportunities for professional development. Normative occupational commitment was differentially, positively associated with the importance ascribed to working in a reputable organisation that is devoted to diversity and social responsibility. Research limitations/implications Additional evaluation using multi‐source and behavioural data would be useful. Practical implications Knowledge of the relationship between types of occupational commitment and desired organisational characteristics among university students could inform organisational positioning relative to recruitment. Originality/value Results reported in this paper demonstrate the potential relevance of occupational commitment components into the processes of recruitment and applicant attraction among university students.
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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 | 0.019 |
| 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) | 0.003 | 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".