The Multiscalar Worlds of Remediation: Sitting Halfway Down a Meandering Path
Bibliographic record
Abstract
This hybrid environmental creative nonfiction invites the reader to consider a small, contaminated patch of land tucked inside an industrial neighborhood in Montréal (Tiohtià:ke). By exploring the multiscalar geographies and histories of this site—now a municipal phytoremediation testbed—I seek to reframe the notion of remediation against the extractive and colonial logics that underpin Western technoscientific imaginaries and practices of healing. Thus, I will address the “pluriverse” as a coalescing of multiple and incommensurable scales of living and non-living, political and affective, and social and economic processes that define a seemingly desolate urban wasteland (Povinelli 2016). Through photography and repeated visits, I consider ancient Carboniferous worlds and persistent toxicants (Hird 2013); Suncor refineries and a neighborhood; soil (Puig de la Bellacasa 2015), trees, bacteria (Hird and Yusoff 2019), and those who inhabit and continue to care for this place.
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 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 | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.036 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".