Adoption of information technology in primary care physicianoffices in New Zealand and Denmark, part 2: historical comparisons
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 is the last in a series of five papers about the use of computing technology in general practitioner (GP) practices in Denmark and New Zealand. This paper introduces a unique comparison instrument developed for this study using the best evidence available namely data was pulled from centralised databases and was indisputable (e.g. percentage of primary care physicians who send medication prescriptions electronically to pharmacies). Where the data was simply not available, estimates were made. Since the reliability of the data on the use of computers by primary care physicians is so variable and in some case simply not available, the authors also introduce the use of a Cochrane-like confidence factor (CF) to each comparison measure. The paper draws particular attention to the fact that both countries have a highly visible central unifying body or what might be called a Health System Integrator; though Denmark s Medcom is a pseudo government agency New Zealand's HealthLink is a private company, both play critical roles in the success story of these two countries.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it