Bibliographic record
Abstract
"This exhibition brings together work by Gabrielle L’Hirondelle Hill and Nicole Kelly Westman along with Toronto-based collective, Faraz Anoushahpour, Parastoo Anoushahpour and Ryan Ferko to look at how histories and economies are inscribed on landscapes, mapping the often hidden power relations held within. Rather than contending with the weight of landscape representation as a nation-building project, each of these works circumvent this logic through intimate and sustained relationship to place. These projects are not about representation, but continued acts of care that stretch through time and across geographies. Each situated in a post-industrial or transitional space, devoid of human habitation or commercial use, these works are punctuated by absence — a hole left by industry, an abandoned mine, a recently resurfaced plot of land — containing traces of what was and fertile for what could be. Through economies of care, investigations into deep history and the creation of speculative futures, these works attempt to answer a question of what could be, re-infusing these absences with the persistence of human presence, unsettling inherited narratives and allowing a polyphonous understanding of our relation to place. " -- Publisher's website.
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 | 0.008 | 0.002 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.226 | 0.149 |
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".