Nullius no more? Valorising vacancy through urban agriculture in the settler-colonial ‘green city’
Bibliographic record
Abstract
Among the brick warehouses and new-build condos of Montreal’s hip Mile-Ex neighbourhood, a group of musicians leads a parade a few dozen strong. The intergenerational crowd comes to a stop and circles together in a gravel-covered vacant lot, chattering happily and bouncing in time to the bass drum and snare, while the band’s clarinets, accordion, cello and tuba crank out a lively tune. A mother flanked by her two young children scrapes away some of the gravel and begins digging holes in the clay beneath. Another woman places a basil plant in one of the holes and pats some soil back around its base. Someone else empties a basketful of ‘seed bombs’ on the ground and calls out for people to come and grab some. A young girl picks up one of the small balls of clay packed with herb and wildflower seeds, walks a few feet, cranks her arm back, and hurls it as if it were a Molotov cocktail, the first of many thrown in this battle, in the words of the event’s organisers, to approprier la ville (‘reclaim the city’). In Montreal, as in cities across North America, it is often not long before some group or other replaces the gravel, asphalt or weeds of a vacant lot with something more verdant: beds of rich soil and compost giving life to leafy vegetables, vines, fruits and flowers. Indeed, the relationship between vacancy and urban agriculture is arguably as old as urban food production itself; city dwellers have always opportunistically gardened or grazed animals on the grass and weeds growing in the ‘wastelands’, those interstitial spaces between and within residential and commercial lots, markets, streets and sidewalks (Vitiello and Brinkley, 2014).
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.
How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".