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
Toronto's Portlands neighborhood is the target of an enormous redevelopment effort that will infuse smart-city technologies into the urban morphology. The quasi-governmental Waterfront Toronto agency has partnered with the Alphabet subsidiary company Sidewalk Labs to plan and build out the neighborhood, essentially from the ground up, and embedded it with sophisticated technologies. The redevelopment plan details a digital layer made up of sensors that will collect and process locational information, tracking movement and usage patterns. Yet the project has been mired in controversy, mainly because of questions about data ownership and management. While there will be the amassing of an unfathomable amount of data, it is not clear who will control it and how it will be processed and used. Critics of the project have pointed out that the potential value of the data is enormous and if a private company has exclusive domain over it, that company could decide to sell it at will. Securely storing citizen’s data is another problem. This paper provides a description of the popular newspaper accounts of the Waterfront Toronto Project. It discusses how the project and redevelopment authority came to be, how Alphabet be-came the primary partner, the redevelopment vision, and controversy that has engulfed this smart-city 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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