Connected in Jane and Finch: a story of the people
Bibliographic record
Abstract
The Jane and Finch neighbourhood in Toronto, Ontario has served as a \ncrucial stepping stone to help new immigrants transition as they move \nto a new country. Initially, the community had essential services and \nsupport systems in place that would have made the transition easier. \nHowever, as the neighbourhood has grown and changed in the past fifty \nyears, it has neglected to evolve these services and support systems to \nsuit the needs of the current demographic. This thesis is an exploration \nof how to ensure that future generations living in Jane and Finch are set \nup for success. It is also a story of the people living in Jane and Finch \nand how to better serve them. By utilizing a methodology that relies \non a creative narrative, a more personal connection to the people and \nneighbourhood is established, allowing for a sensitive design that targets \nthe users’ specific needs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.053 | 0.026 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".