How do values shape technology design? An exploration of what makes the pursuit of health and wealth legitimate in academic spin‐offs
Bibliographic record
Abstract
By actively supporting cooperation between academia, clinical settings and industry, several policy initiatives assume that the two policy agendas of health and wealth can be reconciled through the development of health technology. Our goal in this article is to shed light on the way the concurrent pursuit of health and wealth operates in practice by examining the valuation schemes, actions and decisions that shaped technology development in three Canadian spin-offs. Drawing on the sociology of judgement, our analytical framework conceives of technology development as a purposive collective action that unfolds in a normatively heterogeneous context (one pervaded with both corporate and public service mission values and norms). Our qualitative empirical analyses explore four valuation schemes and their corresponding regimes of engagement that characterise why and how technology developers commit themselves to addressing certain clinical, interactional, organisational and economic concerns throughout the development process. Our discussion suggests that the ability to reconcile health and wealth goals is to be found in the moral repertoires that provide meaning to, and render coherent technology developers' participation in corporate activities driven by economic growth.
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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 | 0.050 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".