Bibliographic record
Abstract
Although the Supreme Court of Canada has described freedom of political, and especially electoral, debate as the most important aspect of the protection of freedom of expression in Canada, no debate in Canadian society is so regulated as that which takes place during an electoral campaign. Parliament has set up—and the Supreme Court has embraced—an “egalitarian model” of elections, under which the amount of money participants in that debate can spend to make their views heard is strictly limited. “Third parties”―those participants in pre-electoral debate who are neither political parties nor candidates for office―are subject to especially strict expense limits. In addition to limiting the role of money in politics, this regulatory approach was intended to put political parties front and centre at election time. This article argues that changes since the development of the “egalitarian model” have undermined the assumptions behind it and necessitate its re-examination. On the one hand, since the 1970s, political parties have been increasingly abandoning their role as essential suppliers in the marketplace of ideas to the actors of civil society, such as NGOs, unions, and social movements. On the other hand, over the last few years, the development of new communication technologies and business models associated with “Web 2.0” has allowed those who wish to take part in pre-electoral debate to do so at minimal or no cost. This separation of spending and speech means that the current framework for regulating the pre-electoral participation of third parties is no longer sufficient to maintain political parties’ privileged position in pre-electoral debate. While the current regulatory framework may still have benefits in limiting (the appearance of) corruption that can result from the excessive influence of money on the political process, any attempts to expand it to limit the online participation of third parties must be resisted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.032 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.011 | 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".