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Record W4386500792 · doi:10.47788/gmty9723

Imagining Air

2023· book· en· W4386500792 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueUniversity of Exeter Press eBooks · 2023
Typebook
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsUniversity of Alberta
FundersArts and Humanities Research CouncilUniversity of ChicagoUniversity of OxfordWellcome TrustNatural Environment Research CouncilUniversity of ReginaPrinceton University
KeywordsInvisibilityVisibilityHistoryNarrativeCoronavirus disease 2019 (COVID-19)Air pollutionEnvironmental ethicsSociologyAestheticsGeographyArtMeteorologyPhilosophyEcologyLiterature

Abstract

fetched live from OpenAlex

Imagining Air tackles air as a cultural, medical, and environmental phenomenon. Its major aim is to explore air’s visibility and invisibility within the environment through the investigation of such phenomena as pollution and pandemics. The book provides environmental and medical perspectives on air, in particular how it has historically been envisioned in U.S., Canadian and British cultural and literary narratives. The authors explore how these representations and the constructed meanings of air can help us understand the complex nature of air as it pertains to the COVID-19 pandemic, air pollution and broader environmental degradation. Chapter authors: Siobhan Carroll, Jeff Diamanti, Corey Dzenko, Clare Hickman, Tatiana Konrad, Jayne Lewis, Chantelle Mitchell, Christian Riegel, Arthur Rose, Gordon M. Sayre, Savannah Schaufler.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.027
Threshold uncertainty score0.804

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.065
GPT teacher head0.247
Teacher spread0.182 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it