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
High Park is one of the largest green spaces within the city of Toronto, and it attracts people from all over the city with its beautiful lawns, attractive gardens, and oak savanna and pond restoration. Walking through the park on a sunny, summer day you encounter the diversity that is the city of Toronto—a city where about 50 percent of the residents are people who immigrated to Canada within the last ten years (Toronto Community Foundation 2004). In 2007, a park planning exercise was led by the park management and the volunteer park council to decide the direction of future park development, and specifically what role ecological restoration would play. Seventy people met on a Saturday morning to discuss the future of the park and gather input from various interest groups, including dog walkers, gardeners, cyclists, and restorationists. All seventy participants were white and seemingly of western European ancestry. They certainly did not reflect the diversity of the park’s users. Looking around the room, I questioned why diverse cultures were not engaged in this process even though they had direct interest in what happened in the park.
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 | 0.000 | 0.000 |
| 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