Health Care Technology Adoption and Diffusion in a Social Context
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article highlights mechanisms that may further sustainable technological development for the 21st century. The distributional effects associated with the adoption and diffusion of health care technologies are addressed wherein the capacity to capitalize on the health gains from the adoption of technology varies in society. These effects are caused by the actions of individuals as they segment themselves into distinct social groups. The circumstances under which social institutions are further segmented are explored and may motivate public sector limits on the funding for and diffusion of health care technologies. Safety and efficacy benchmarks are necessary but insufficient conditions for sustainability as product advantage on grounds of cost-effectiveness must also be demonstrated. Furthermore, given the substantial role played by public sector decision makers in purchasing health care technologies, the distributional consequences associated with the uptake and diffusion of technology need to be gauged by product designers and those responsible for marketing.
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.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.004 |
| 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 it