Bibliographic record
Abstract
As we prepare to ring out 2008, here are a few thoughts about some of the leading stories that have shaped Taiwan during the past year: 1. Back and Blue: Ma Ying-jeou sweeps into office as Taiwan’s new president, winning a convincing majority of the popular vote based on a platform promising a more stable relationship with China, economic prosperity, and clean government. Cross-Straits tensions have declined markedly, while the opening of direct links should bring great benefits to the citizens of both China and Taiwan. At the same time, however, the economy remains in the doldrums (see #2) and there are also concerns about the future of the judicial system (see #3). The KMT’s return to power has also witnessed the rehabilitation of Chiang Kai-shek’s reputation (plus the name of his memorial hall), attempts to interfere with the mass media, and occasional expressions of anti-Japanese nationalism. 2. Hard Times: The TAIEX, once expected to top 10,000, is now languishing in the 4,000s, but it’s the working class that is truly suffering. As of November, the number of men and women who had lost their job had topped the half million mark, with Taiwan’s 4.6% unemployment rate being one of the highest in East Asia and having the dubious distinction of topping the four little dragons. Other workers are being forced to take long periods of unpaid leave, which allows them to keep their jobs but not earn enough money to make ends meet. It looks to be a cold, dark winter, but hopefully things will improve once the world economy rebounds.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.266 | 0.107 |
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".