“Nailing it Across the Board”: Negotiating Identity as Trades Teachers
Bibliographic record
Abstract
A vocational identity of teacher has been linked in research to teaching efficacy, job satisfaction, and commitment to the profession. For postsecondary college instructors, teaching is most often a second career, with the first career providing the subject matter expertise that is the foundation of the second. The first career also carries an established vocational identity, leading to a negotiation of that concept with the new identity of teacher. This article presents recent doctoral research exploring vocational identity among postsecondary trades teachers in Western Canada. The exploratory mixed-methods study found the two identities of tradesperson and teacher were interconnected, with teaching seen by study participants as part of being a journeyperson, and the identity of tradesperson seen as essential to teaching in vocational education. An understanding of this negotiated interconnection provides insight for colleges in the hiring, training, and retention of trades teachers.
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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 | 0.013 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.035 | 0.035 |
| Scholarly communication | 0.016 | 0.010 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".