Bibliographic record
Abstract
What can a parking pad at the front of a house and agent orange, a defoliant used by the US military in its "Operation Ranch Hand" during the war in the Vietnam, possibly have in common?How unsafe does everything need to become to justify action?These are just a few of the questions at the centre of the stories I share in this piece; a piece that traces my/our experience trying to "get" something from our city to make access happen, and another story from decades earlier centred on restorative justice and the toxic chemical (dioxin) legacy of the American war in Vietnam.The application form for a front yard parking pad does not have a check box for 'disability' or 'accessibility' … of course it doesn't, so what next?How do I make visible our needs, as a family with a disabled child, within an ableist, bureaucratic, technocratic city services process, that does not 'see' us, a family that needs to remake their front yard to make it work for us and our daughter, to make access possible.If you were to visit our street in Toronto, Canada, what you would see at most homes, is a front yard parking pad.In our case, however, this parking pad process begins with a battle pitting us against the urban forest.A tree sits on the city side of the front yard, planted by a previous occupant.The tree's contribution to the urban forest is negligible, it is not one of the beautifully massive ageing oaks or elms tasked with casting shade across our neighbourhood in the heat of summer; it is an ageing multi-trunk birch tree … a professional arborist has said it doesn't have much time left.Because of said tree, we begin a political project to organize support for our plan -noting that we can build around the tree.I begin to pursue our
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.132 | 0.040 |
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".