Key trends in interprofessional research: A macrosociological analysis from 1970 to 2010
Bibliographic record
Abstract
The field of interprofessional research has grown both in size and in importance since the 1970s. In this paper, we use a macrosociological approach and a Bourdieusian theoretical framework to investigate this growth and the changing nature of the field's research. We investigate publication trends at the aggregate (field) level, using an original dataset of 100,488 interprofessional-related articles published between 1970 and 2010 and recorded in the PubMed database. Articles were coded using a list of 638 codes that were then analyzed thematically and longitudinally. Our results are presented in two main sections. Initially, we consider the growth and reach of the interprofessional field. Second, we explore the five different trends ("terminological issues", "rising management rhetoric", "expansion of psychometrics", "shift from individualism to collectivism" and "emerging issues") that emerged out of our thematic analysis of publications over time. These findings are discussed in the light of Bourdieu's framework to provide an indication of what we argue is a growing legitimacy of the field of interprofessional research as a scholarly domain in its own right.
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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 | 0.008 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.042 | 0.070 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".