Bibliographic record
Abstract
This paper compares three recent government apologies made to indigenous peoples in Australia (2008), Canada (2008), and the U.S. (2009). All of these apologies were the second iterations of earlier ones made in Australia in 1997, Canada in 1998, and the U.S. in 2003 paper compares the texts and contexts of these apologies (who delivered them and in what setting and to what audience), and the political dynamics associated with them to assess the meaning and effectiveness of apologies as a first step toward achieving political reconciliation and intercultural justice. It addresses how and why the first and second versions of the apologies in each country differed, and tries to explain why the Canadian apology, the only one of the three apologies that was accompanied by compensation, was the most robust of the three, and why the U.S. apology was the weakest of the three. paper also analyzes these three recent apologies in terms of what some scholars have termed The Age of Apology, or the increasingly frequent attempts to address grievances arising from wrongs committed by oppressive or genocidal actions between nations, or between races within nations, by using an apology.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.020 | 0.029 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".