Bibliographic record
Abstract
The idea for this book was planted in my mind in 1996 while I was attending the Royal Thai Army's Command and Staff College in Bangkok, Thailand.There I met my wife, Judith Steiner, a Canadian of anglophone and francophone background who was working in Bangkok for a Hong Kong-based international firm.One of the things that our relationship made me realize was how much Australians and Canadians have in common and just how little we both realize it.The Thais were very gracious and I made many enduring friendships during my time in their country.But it was towards those with whom I have more in common culturally that I was predisposed to gravitate in my spare time.This phenomenon, to me, was striking.While we were away from our own countries, what struck us most was our common ground, rather than the distinctive cultural and geographic nuances that are more apparent when one is at home.Yet various social commentators have little use for a close focus on the ties that make such gatherings almost naturally occurring events.Instead, for instance, Australian academics, government policy writers, and social engineers spent much of the 1990s trying to convince themselves and the world that they were Asians.Clearly, Australia will always have a place in Asia, but that fact should not lead to a denial of cultural affinities and strategic predispositions that have for many years included alliance with the United States and close association with the world's English-speaking nations.In the meantime, Canadians, generally speaking, have experienced similar angst about their place in the world.Canadians appear to have spent many years trying to tell themselves that they are anything but Americans.Figuring out what is distinctive for Canadians or Australians has been a frequent topic of discussion for the members of these New World nations.Yet, apart from a select number of Canadian or Australian scholars, few have paid much attention to their commonalities.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.471 | 0.264 |
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".