Bibliographic record
Abstract
Purpose – In response to the conclusions of a meta-analysis of career success studies (Nget al., 2005), the purpose of this paper is to expand the range of variables being examined as predictors of career success by weaving the person-organization fit and external marketability perspectives into current career success frameworks. Design/methodology/approach – A survey was administered in partnership with an association of human resource professionals located in Canada. The questionnaire was transmitted electronically to human resource professionals. The final sample included 546 full-time, permanent, human resource professionals from multiple organizations. Findings – Confirmatory factor analysis supported the measurement model. In the final structural model, external marketability exerted a significant direct effect on career success. Person-organization fit was strongly associated with organizational sponsorship. Organizational sponsorship, in turn, exerted a significant effect on subjective career success. Originality/value – This study contrasted and tested two theoretical perspectives on career success. The mediated indirect association between person-organization fit and career success provided support for the rationale of the sponsored mobility model of social advancement. The direct association between external marketability and career success suggests that success can be achieved even without organizational sponsorship on the basis of expressions of one’s human capital.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.031 | 0.063 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".