Bibliographic record
Abstract
ism and marketing board claimed that the number of visitors was three times greater in the first quarter of 1993 than twelve months earlier. More dramati-cally, the growth in revenue from tour-ism had increased fivefold during the period. There were plans to transform the government administration center into a shopping complex, a project to be funded by the island's Development Finance Committee. A television and radio studio was being built with Aus-tralian support, permitting the island to develop its own broadcasting facili-ties. The first private enterprise news-paper, the Niue Star, was launched in 1993, backed by printer-publisher Michael Jackson. An initiative by a Catholic priest, Father Glover, developed into a small, environ-mentally friendly industry, as Niue shipped its empty aluminum cans to New Zealand and its bottles to West-ern Samoa. In Tuapa, however, the judgment on the government's efforts was far from favorable. The by-election saw an experienced member of the Young Vivian camp, Fisa Pihigia, win the seat, capitalizing on antigovernment sentiment stemming largely from economic difficulties. The result left the government in a precarious position, its fragile one-seat majority jeopardized by unattractive options and significant economic con-straints.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.300 | 0.191 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".