Learning and professional acculturation through work: Examining the clinical learning environment through the sociocultural lens
Bibliographic record
Abstract
Purpose: We examined studies of the clinical learning environment from the fields of sociology and organizational culture to (i) offer insight into how workplace culture has informed research on postgraduate trainee learning and professional development; (ii) highlight limitations of the literature; and (iii) suggest practical ways to apply sociocultural concepts to challenges in the learning environment.Materials and methods: Concepts were explored by participants at a consensus conference in October 2018.Results: We identified three enduring foci for research using a sociocultural lens: the hidden curriculum, exploration of medical errors, and the impact of time pressures on the relational nature of clinical education. Limitations included the lower value attributed to informal learning and a pejorative valuation of the hidden curriculum; and disconnect between practices in clinical settings and the priorities of the larger organization.Conclusions: Research on the learning environment using a sociocultural lens suggest workplace goals, norms and practices determined which learners engage in learning-relevant activities, to what extent, and the degree of guidance provided, with these factors creating “tacit” curricula that may support or compete with formal learning goals. We close with guidance on how sociocultural constructs could inform research to improve the learning environment.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".