Moving ideas? The news media’s impact on ridehailing regulation in Canadian cities
Bibliographic record
Abstract
ABSTRACTOver the last 5 years, regulating ridehailing has risen to the top of the agenda in nearly every major city. There is an established academic literature that speaks to how traditional news media shapes and informs the regulatory agenda for municipalities. Building off this literature, we investigate the role that traditional news media played in shaping the debate about regulating ridehailing in Canadian cities. After searching and analyzing the news media coverage of six major events and four general themes in eight major news media publications in Toronto, Montreal, and Vancouver, we conclude that publications rarely took a consistent political/ideological viewpoint. We offer three non-mutually exclusive contributory factors to explain our results, however, the authors would like to emphasize that consolidation and profit-maximizing behavior in the news industry have led to the relinquishment of news media’s historical role in municipal agenda-setting.KEYWORDS: Ridehailingagenda settingnews mediamunicipal governmentmedia analysis AcknowledgmentsWe would like to thank Jarret Meyers who served as a research assistant on this project.Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1. In most parts of Canada, regulating vehicle-for-hire services is a local responsibility. For instance, the City of Toronto has exclusive jurisdiction over the vehicle-for-hire industry and can regulate both taxicabs and ridehailing services. However, the regulation of vehicle-for-hire services in Quebec and British Columbia concentrates significant power in the hands of provincial institutions.2. This article focuses mainly on the influence of traditional news outlets, namely established newspapers in each major market in the county, as well as a national media outlet. Throughout the paper, we use the term “news media” to refer to these outlets, which have both traditional paper and digital properties. This term does not refer to social media, blogs, or other new forms of media as they are not established authoritative sources.3. Broadsheet and tabloid are newspaper nomenclature referring to printing styles. They do not refer to a level of journalistic quality, as used in common language.4. We confined our examination to established news media outlets that had established city hall press offices and set editorial teams. This excluded alternative weekly and largely digital publications, such as NOW and the Tyee.5. We chose this methodology because of the speed at which the news media cycle moves on from each story. Most newspapers only had a single article published for each tag. Others had a few. However, we intended to capture the initial reaction of the news media on each given story, so we focused on the first story from each outlet for each tag.Additional informationNotes on contributorsAustin ZwickAustin Zwick is an Assistant Teaching Professor at the Maxwell School of Citizenship & Public Affairs and the Assistant Director of the Policy Studies Program. He holds a PhD in Planning from the University of Toronto. Zwick’s research focuses on social, economic, and governance transformation brought about by technological advancement.Zachary SpicerZachary Spicer is an Associate Professor in the School of Public Policy and Administration at York University. His research focuses on urban governance and public policy. He holds a PhD in Political Science from The University of Western Ontario and completed post-doctoral fellowships at Wilfrid Laurier University and the University of Toronto.Mischa YoungMischa Young is an Assistant Professor in the Department of Urban Environments at the Université de l’Ontario français. His research focuses on the future mobility—of both goods and individuals—within the urban landscape. He holds a PhD in Planning from the University of Toronto and a postdoctoral research fellowship from the University of California, Davis.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".