Open Data and Open Governance in Canada: A Critical Examination of New Opportunities and Old Tensions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
As governments develop open data strategies, such efforts reflect the advent of the Internet, the digitization of government, and the emergence of meta-data as a wider socio-economic and societal transformational. Within this context the purpose of this article is twofold. First, we seek to both situate and examine the evolution and effectiveness of open data strategies in the Canadian public sector, with a particular focus on municipal governments that have led this movement. Secondly, we delve more deeply into—if and how, open data can facilitate more open and innovative forms of governance enjoining an outward-oriented public sector (across all government levels) with an empowered and participative society. This latter vantage point includes four main and inter-related dimensions: (i) conceptualizing public value and public engagement; (ii) media relations—across traditional intermediaries and channels and new social media; (iii) political culture and the politics of privacy in an increasingly data-centric world; and (iv) federated architectures and the alignment of localized, sub-national, and national strategies and governance mechanisms. This article demonstrates how each of these dimensions includes important determinants of not only open data’s immediate impacts but also its catalytic ability to forge wider and collective innovation and more holistic governance renewal.
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.
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 | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 it