Who am I? Key influences on the formation of academic identity within a faculty development program
Bibliographic record
Abstract
INTRODUCTION: Professional identity encompasses how individuals understand themselves, interpret experiences, present themselves, wish to be perceived, and are recognized by the broader professional community. For health professional and health science educators, their 'academic' professional identity is situated within their academic community and plays an integral role in their well being and productivity. This study aims to explore factors that contribute to the formation and growth of academic identity (AI) within the context of a longitudinal faculty development program. METHODS: Using a qualitative case study approach, data from three cohorts of a 2-year faculty development program were explored and analyzed for emerging issues and themes related to AI. RESULTS: Factors salient to the formation of AI were grouped into three major domains: personal (cognitive and emotional factors unique to each individual); relational (connections and interactions with others); and contextual (the program itself and external work environments). DISCUSSION: Faculty development initiatives not only aim to develop knowledge, skills, and attitudes, but also contribute to the formation of academic identities in a number of different ways. Facilitating the growth of AI has the potential to increase faculty motivation, satisfaction, and productivity. Faculty developers need to be mindful of factors within the personal, relational, and contextual domains when considering issues of program design and implementation.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".