Career and Mentor Satisfaction among Canadian Engineers: Are there Differences based on Gender and Company‐Specific Undergraduate Work Experiences?
Bibliographic record
Abstract
Abstract In 2005, an in‐depth study was undertaken to collect quantitative and qualitative data on the career attitudes of Canadian engineers in the province of Manitoba. This paper examines the quantitative data on the relationships between prior undergraduate work experiences with their current employers and male and female respondents' career and mentor satisfaction. The results suggest that undergraduate work experience programs may play a role in enhancing engineers' perceptions of their recognized authority/expertise within their field. Results also show that prior work experience with current employers is related to satisfaction with mentors. Furthermore, a significant interaction effect was found for both prior work experience and gender as they relate to mentor satisfaction. Female engineers with prior work experience were the most satisfied with their mentors, while those without prior work experience were the least satisfied. Findings point to the value of company‐specific undergraduate work experience as a socialization tool and the role it plays in nurturing long‐term career development, particularly for young women engineers.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".