ASEAN benchmarking in terms of science, technology, and innovation from 1999 to 2009
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 provides an empirical assessment of the performance of the member states of the Association of Southeast Asian Nations in terms of science, technology, and innovation. This study is relevant because it employs a larger data set, examines more countries, and covers more years than previous studies. The results indicate that these countries had differing patterns of performance, and the pattern of growth among them was asymmetrical. Additional findings suggest that these countries performed idiosyncratically with respect to the six quantitative dimensions we examined. Our research includes a form of comparative policy evaluation that might assist the monitoring of the implementation of "Vision 2020". The results simplify how we determine the relative strengths and weaknesses of national innovation systems and are relevant to policy discussions. In relation to transferability, the findings demonstrate similarities to the European Union with regard to performance and governance.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.026 | 0.054 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it