Eleksin: the 1987 national election in Papua New Guinea
Bibliographic record
Abstract
In 1987, Papua New Guinea held its sixth national election; its third since Independence in 1 975. Each one of the previous elections was the subject of a book, to which many students of Papua New Guinea contributed (Bettison, Hughes and van der Veur 1965; Epstein, Parker and Reay 1971 ; Stone 1 976; Hegarty 1977; King ). They constitute a remarkable record and make it possible to trace the evolution of PNG politics in greater detail than in many developed countries. This study of the 1987 election owes a great deal to those that went before it, but a deliberate decision was taken not to try to replicate them. Had one wanted to do so, it would have been difficult, for each of the previous studies differed from all the others. Nevertheless, some constants can be found. Every study included one or more chapter on the overall significance of the election. In addition, each one included constituency studies, where the local level, the competition amongst candidates, was the focus. The present volume follows its predecessors to that extent.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".