<i>The Adaptable Country: How Canada Can Survive the Twenty-First Century</i>, Alasdair Roberts
Bibliographic record
Abstract
Like others before him, Alasdair Roberts has decided it is time for a sober look at Canada’s political architecture in light of the social and economic challenges the country is facing. These challenges cannot receive a constructive response without a vibrant and resilient political system. But at the moment, the country suffers from a lack of national strategy, a weakened public service, a fragmented political elite, and an inadequate capacity for democratic deliberation. While there may be no “solutions” to these problems, Roberts assures us that there is ample room for improvement. Improvement will not (and should not) come in the form of a revolutionary rescue, but in the reinvigoration of Canada’s federal–liberal–democratic system. In contemplating reform, Roberts argues, Canadians should be realists: accept that rapid shifts in circumstance are inevitable and embrace a deliberate change strategy focused on strengthening the country’s political apparatus. Although this apparatus is adaptable, adaptation is not automatic. For Canada to be The Adaptable Country, Canadians need to invest in new institutional arrangements, rediscover old ones, and adopt practices that make the most of a decentralized, executive-dominated democracy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.027 | 0.009 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.023 | 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".