Bibliographic record
Abstract
As David Webster observes in Challenge the Strong Wind, most Canadians do not feel an instinctive interest in East Timor.It is a distant country on the other side of the world, a fragment of the Portuguese colonial empire.It was also a problematic country for Canada, complicating our relationships with more important states and inconveniencing the Canadian government at home.East Timor was, however, a significant country for Canadians because it was invaded and annexed by its much bigger neighbour, Indonesia, and kept in brutal subjection for almost a quarter of a century.The record of Indonesian atrocities, once established, stimulated -perpetuated -discordant voices in Canada and other western democracies that annoyed and increasingly embarrassed the Canadian government.When Webster writes about the Canadian government, he means more than a passing aggregation of politicians.The Canadian cabinet had no policy on East Timor as such.The politicians are concerned with other issues and bigger countries, and Webster illuminates the hierarchy of attention: the United States, Western Europe, the Cold War, the arms race, and bilateral and multilateral trade -tangible subjects with material or political impacts at home.Realism in a classic sense informs and defines Canada's foreign policy and external relations.But, as analysts of foreign policy in Canada and elsewhere have repeatedly shown, there are other considerations -ethical and humanitarian ones -that give purpose to policies.This,
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.633 | 0.548 |
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".