Career transitions and their causes: A country‐comparative perspective
Bibliographic record
Abstract
This empirical paper investigates how individuals conceptualize causes of career transitions, focusing on the three European countries of Austria, Serbia, and Spain in comparison to the USA and China. Collectively, these countries represent four separate cultural regions according to Schwartz. Semi‐structured interviews were conducted with members of three occupational groups: business people, nurses, and blue‐collar workers. Analysis of the data generates greater insight about the existence of both region‐specific patterns as well as potentially universalistic tendencies regarding perceived causes of career transitions. Perceptions of internal (to the person) drivers of career transitions as activating forces are evident in all five countries. The overall results support contemporary notions of occupational careers that are highly individualized, a characterization strongly emphasized in the current career literature. In the European culture clusters, causes of career transitions are attributed internally and externally. China, representing the Confucian cultural region, stresses external causes for career transitions. By contrast, in the USA only internal attributions of causes are reported.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".