An Exploration of Career Script Awareness Within the Academic Career
Bibliographic record
Abstract
As individuals seek to make career decisions, they rely on career scripts to guide them towards successful and prosperous careers. However, career scripts can only guide individuals successfully when they are complete and/or accurate. Individuals may face career-related challenges when making decisions with limited awareness of the appropriate script. From the perspective of an academic career, individuals are presented with incomplete career scripts at various stages of their academic career. This study takes two approaches to assess how individuals are made aware of the teaching component of an academic career script. Conducting content analysis on promotion documents of 183 higher education institutions from Ireland, the UK, the US, Australia, Canada, and New Zealand, we identify how important teaching is for promotion. From here, we conduct a systematic literature review to determine how teaching requirements are approached at the education and recruitment stages of the career. Our study found that while teaching plays an important role in the awarding of promotion, individuals starting out, are presented with limited to no awareness of the importance of teaching to their careers. Additionally, they are presented with limited exposure during the early stages of their first faculty appointments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".