An Exploratory Case Study: Constraints and Opportunities to Women Entering Nontraditional Career Pathways
Bibliographic record
Abstract
Providing equal opportunities for female students to pursue non-traditional careers is an important issue facing the Alberta educational system. The purpose of this exploratory case study at one high school in northern Alberta was to understand why so few female high school industrial arts students choose careers in certain male-dominated trades areas such as welding, mechanics, and machining. The conceptual frame of this exploration was women’s career choice options viewed through four foci: (a) education and policy, (b) opportunities for women to choose careers, (c) constraints for women to choose careers, and (d) women’s voices to express and understand the problem. For data collection, 6 former female industrial arts students participated in semistructured interviews and wrote responses to a 15-question questionnaire. Participants reported that few or no barriers exist for women who want to enter non-traditional careers and that career paths are based on women’s choices and the attractiveness or lack thereof at an individual level to the type of work performed. Findings provide northern Alberta educators, administrators, curriculum developers, and policymakers with increased understanding and insight into why some women choose to forego entering certain trades areas even though they have demonstrated competence and aptitude for the work. This study’s iterations shifted from a perceived need to advocate for women to the realization that participants wanted to have a voice and be supported rather than continue to be marginalized as result of having teachers not consider their opinions important or valid. Findings are not generalizable to other contexts; thus, further inquiry in a broader context is recommended to gain increased clarity and understanding of the problem and possible solutions.
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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".