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
This document intends to guide city stakeholders (public officials, civil society, technology innovators, private sector, academics, residents, etc.) toward formulating and strategically aligning practices with their agreed upon and unique Open Smart City vision. The Open Smart City definition and guide are relevant to city leaders and community leaders at multiple levels of governance (e.g., provincial, territorial, and federal). This is part of a series of documents from the Natural Resources Canada GeoConnections funded Open Smart Cities project at Open North and led by Dr. Tracey P. Lauriault in collaboration with Jean-Noe Landry and Rachel Bloom of Open North. Open Smart Cities in Canada is a collaborative project. We would like to thank smart city representatives from the cities of Edmonton, Guelph, Montréal, and Ottawa and officials from the provinces of British Columbia and Ontario for sharing their time, expertise, and experiences with us. Furthermore, this project benefits from contributions made by the project’s core team of experts and researchers. We are grateful to Professor David Fewer, LL.M., (Canadian Internet Policy and Public Interest Clinic (CIPPIC)), and Professor Mark Fox (University of Toronto) for providing their expert advice on the design of research and its outputs. Finally, we thank graduate students Stephen Letts and Carly Livingstone (Carleton University) for research assistance and editing over the course of the project.
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 | 0.000 | 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 | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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