Bibliographic record
Abstract
Abstract Asia Pacific Economic Cooperation (APEC) is an intergovernmental forum for increasing trade and investment as well as economic cooperation in the Asia Pacific region. It began in 1989 as a series of annual meetings of foreign and trade ministers from 12 member economies (the five industrialized economies of Australia, Canada, Japan, New Zealand, and the United States, the Republic of Korea, and the six ASEAN members of Brunei Darussalam, Malaysia, Indonesia, the Philippines, Singapore, and Thailand), focusing on economic cooperation. Three Chinas (the People's Republic of China, Hong Kong, and Chinese Taipei) joined in 1991. Since the first Economic Leaders' Meeting in Seattle in 1993, APEC leaders declared that they would achieve “free and open trade and investment in the region.” In 1994 they declared ambitious Bogor Goals, setting a deadline for achieving them by 2010 for industrialized economies and by 2020 for the rest of the members. The Osaka Action Agenda was adopted in 1995, and since 1997 each member economy has been submitting an annual Individual Action Plan (IAP) detailing their actions to meet the Bogor Goals and implementing them.
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.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.141 | 0.076 |
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".