Louder than words: power and conflict in interprofessional education articles, 1954–2013
Bibliographic record
Abstract
CONTEXT: Interprofessional education (IPE) aspires to enable collaborative practice. Current IPE offerings, although rapidly proliferating, lack evidence of efficacy and theoretical grounding. OBJECTIVES: Our research aimed to explore the historical emergence of the field of IPE and to analyse the positioning of this academic field of inquiry. In particular, we sought to investigate the extent to which power and conflict - elements central to interprofessional care - figure in the IPE literature. METHODS: We used a combination of deductive and inductive automated coding and manual coding to explore the contents of 2191 articles in the IPE literature published between 1954 and 2013. Inductive coding focused on the presence and use of the sociological (rather than statistical) version of power, which refers to hierarchies and asymmetries among the professions. Articles found to be centrally about power were then analysed using content analysis. RESULTS: Publications on IPE have grown exponentially in the past decade. Deductive coding of identified articles showed an emphasis on students, learning, programmes and practice. Automated inductive coding of titles and abstracts identified 129 articles potentially about power, but manual coding found that only six articles put power and conflict at the centre. Content analysis of these six articles revealed that two provided tentative explorations of power dynamics, one skirted around this issue, and three explicitly theorised and integrated power and conflict. CONCLUSIONS: The lack of attention to power and conflict in the IPE literature suggests that many educators do not foreground these issues. Education programmes are expected to transform individuals into effective collaborators, without heed to structural, organisational and institutional factors. In so doing, current constructions of IPE veil the problems that IPE attempts to solve.
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 | 0.017 | 0.102 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.045 | 0.045 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".