Rethinking Digital Politics in Canada: Challenges for Law and Policy
Bibliographic record
Abstract
Digital technologies are influencing almost every aspect of Canada's political life and posing new challenges for democratic governance.Recent bills have proposed to expand the powers of existing regulators and to create new ones. 1 Given the wide-ranging impact of digital technologies on Canadian politics and the potential for new legislation to consequentially (maybe even fundamentally) reshape this landscape, this is an area ripe for research by Canadian political scientists.Most of the research on digital technology and politics, however, is US-focused, and that which is concerned with Canada is largely taking place within the field of media and communication studies.Nevertheless, this literature should be of interest to political scientists because the questions it raises are amenable to research within analytical frameworks for the study of public policy.Tamara Small and Harold Jansen's recent edited volume, Digital Politics in Canada: Promises and Realities, is an effort by two pioneering political scientists to bring together a multidisciplinary set of authors to examine how technology is changing politics in Canada.They set out to "take stock of two decades of digital technologies usage by Canadian political actors and institutions," which "has not been done before" (6).Given the lack of comparable texts in the field by political scientists, one can take them at their word.The book follows in the footsteps of work by media scholars such as the late David Taras (see Taras, 2015), the author of the book's preface.It aims to examine the ways in which digital technologies are reshaping the behaviour and strategies of political actors in Canada.Digital Politics covers a range of relevant topics, including the delivery of government services, institutional transparency, voting, security and surveillance, political parties, and the role of civil society and social movements in Canadian politics.The unifying concept of "digital politics" is simply intended to mean the political uses of technology.The question asked by the editors, and indeed by each of the contributors, is whether we should regard the growing influence of digital technology on our political life as a boon to democracy or as a risk.This question is presented in relation to hypotheses of "cyber-pessimism" and "cyber-optimism."Cyber-optimists anticipate
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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 | 0.011 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.027 | 0.020 |
| Scholarly communication | 0.025 | 0.008 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.017 | 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".