Career success and satisfaction: a comparative study in nine countries
Bibliographic record
Abstract
Purpose This project aims to examine levels of career and life satisfaction among successful women in nine countries in the Americas. Design/methodology/approach A structured survey and in‐depth interviews were used, and a variety of occupations, demographics, and personality characteristics assessed – 1,146 successful women from nine countries in the USA responded the survey: 105 from Argentina, 210 from Brazil, 199 from Canada, 84 from Chile, 232 from Mexico, 126 from the USA, and 190 from three countries in the West Indies (Barbados, Jamaica, SVG). Findings Results show no differences in satisfaction based on occupation or country and most demographic variables investigated did not have a significant relationship with satisfaction. Age had a small, significant, relationship, with satisfaction increasing with age; married women were significantly more satisfied than single women. Higher scores on self efficacy and need for achievement, and a greater internallocusof control were all related to higher levels of satisfaction. The relationship between career satisfaction and general life satisfaction was stronger in Argentina and Chile that in the other countries. Originality/value Extends understanding of professional success and satisfaction, in terms of demographic variables and personality, as well as geographically.
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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 | 0.001 | 0.002 |
| 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".