Legitimacy as Social Infrastructure: A Critical Interpretive Synthesis of the Literature on Legitimacy in Health and Technology
Bibliographic record
Abstract
BACKGROUND: As technology is integrated into health care delivery, research on adoption and acceptance of health technologies leaves large gaps in practice and provides limited explanation of how and why certain technologies are adopted and others are not. In these discussions, the concept of legitimacy is omnipresent but often implicit and underdeveloped. There is no agreement about what legitimacy is or how it works across social science disciplines, despite a prolific volume of the literature centering legitimacy. OBJECTIVE: This study aims to explore the meaning of legitimacy in health and technology as conceptualized in the distinctive disciplines of organization and management studies, science and technology studies, and medical anthropology and sociology, including how legitimacy is produced and used. This allows us to critically combine insights across disciplines and generate new theory. METHODS: We conducted a critical interpretive synthesis literature review. Searches were conducted iteratively and were guided by preset eligibility criteria determined through thematic analysis, beginning with the selection of disciplines, followed by journals, and finally articles. We selected disciplines and journals in organization and management studies, science and technology studies, and medical anthropology and sociology using results from the Scopus and Web of Science databases and disciplinary expert-curated journal lists, focusing on the depth of legitimacy conceptualization. We selected 30 journals, yielding 796 abstracts. RESULTS: A total of 97 articles were included. The synthesis of the literature allowed us to produce a novel conceptualization of legitimacy as a form of social infrastructure, approaching legitimacy as a binding fabric of relationships, narratives, and materialities. We argue that the notion of legitimacy as social infrastructure is a flexible and adaptable framework for working with legitimacy both theoretically and practically. CONCLUSIONS: The legitimacy as social infrastructure framework can aid both academics and decision makers by providing more coherent and holistic explanations for how and why new technologies are adopted or not in health care practice. For academics, our framework makes legitimacy and technology adoption empirically approachable from an ethnographic perspective; for decision makers, legitimacy as social infrastructure allows for a practical, action-oriented focus that can be assessed iteratively at any stage of the technology development and implementation process.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".