Bibliographic record
Abstract
I have long felt the need for documentation on the global development—I could probably pin it to the moment I was visiting health technology assessment (HTA) institutions in the United States in 1995, and was looking forward to a trip to the Office of Technology Assessment, only to be told it had just been shut. Instead, I visited the Office of Health Technology Assessment in Washington. In addition, I have observed that some regular attendees of annual meetings of International Society of Technology Assessment in Health Care (ISTAHC) and then Health Technology Assessment International (HTAi), have been slowly dropping out, so that a lot of the history as well as their valuable experiences and expertise have been lost. To be fair, studies have been written about specific HTA institutions, programs, countries, and even regions. Attempts have also been made to chart the history of HTA, but these have, however, fizzled out. Why is this important? Going back to my personal experience, when I first set out to establish HTA in Malaysia, I was plagued with several questions—apart from the obvious one about what HTA really meant, there were others like what organization structure should it have, what should be the work process, how could HTA be used, to name a few. I needed to know what the options were, for example, in coming up with an organizational structure, and to understand these options I would need to look at organizational models in other countries—should it be a national office with regional offices like the Canadian model, or a fully public agency but not within the department of health, like the Swedish model, or an almost independent agency like the Catalan agency in Barcelona. In the absence of a detailed account with the information I sought, I actually had to physically visit various agencies to study their organizational structure, work process, and application, to hear of the challenges they faced, and to learn from their experiences of what could work and what may not.
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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 | 0.084 | 0.405 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.010 | 0.013 |
| Science and technology studies | 0.011 | 0.038 |
| Scholarly communication | 0.021 | 0.037 |
| Open science | 0.012 | 0.010 |
| Research integrity | 0.073 | 0.111 |
| Insufficient payload (model declined to judge) | 0.018 | 0.005 |
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".