Bibliographic record
Abstract
This article delves into the history of petrochemical-derived gas emissions in Toronto, focusing on their emergence and regulation from the end of World War II and up to 1980. Drawing on archival materials, I trace local knowledge production through four loosely defined periods: 1950’s nuisance and ephemerality, 1960’s threshold thinking, 1960’s reactivity and technoscience, and 1970’s ambient intensities. Building on feminist science and technology studies perspectives, particularly Max Liboiron’s concept of managerial ontologies, and M. Murphy’s notion of regimes of perceptibility, I explore key moments when technoscientific logics within a permission-to-pollute system have invisibilized material registers of petrochemical harm, including uneven raced and classed exposures. I reflect on how approaches to air pollution research and governance transitioned from taking citizen sensory knowledge of pollutants seriously through a nuisance complaint framework to increasingly normalizing continuous exposure and treating the atmosphere as a diffusion space for gases. Consequently, I argue that this sets the stage for an enduring belief that long-term, low-level chemical exposures to volatile organic compounds (VOCs) require little mitigation as they self-attenuate. Overall, I underscore the ongoing historical impacts of the notion of the atmosphere as a sink for pollutants on the present governance of petrochemical gases, advocating for further critical engagement with how permission-to-pollute systems are harbored within taken-for-granted atmospheric concepts.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Science and technology studies Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Qualitative | low |
| gpt | Science and technology studies Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: yes | Theoretical or conceptual | low |
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.103 | 0.018 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".