Bibliographic record
Abstract
PREAMBLE: PIERRE TRUDEAU'S ETHOS OF CIVIC PARTICIPATION The question I address in this chapter is the following: Is it possible to establish communicative networks of reciprocal elucidation between public philosophy and civic freedom in our present age that not only are imperial but also have undergone a recent communications revolution? I open with a form of civic ethics that was articulated prior to the communications revolution. At the heart of former Canadian Prime Minister Pierre Trudeau's ethics is the activity of paddling against the current. As early as 1944, in ‘The Ascetic in a Canoe’, he said the ideal of paddling against the current is ‘the resolve to reach the saturation point. Ideally, the trip should end only when the paddlers are making no further progress within themselves.’ What does this ethic mean in practice today? In the 1980s Trudeau campaigned for nuclear disarmament, downsizing military–industrial complexes, resisting the media's glorification of violence as the means to resolve disputes, and for the turn to peaceful and dialogical means of coping with disagreement. He saw this campaign for human security through peace and dialogue as a part of the civic ethics he had always practised. He said that he opposed big concentrations of power: superpowers, military–industrial complexes, media conglomerates, big corporations and the enormous global inequalities these power networks enforce. His means of opposing big concentrations of power was to empower all citizens to participate in the democratic struggles for freedom and equality.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.037 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".