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Record W2998002314 · doi:10.5130/csr.v25i2.6941

Breathing in the Anthropocene: Thinking Through Scale with Containment Technologies

2019· article· en· W2998002314 on OpenAlexaff
Alison Kenner, Aftab Mirzaei, Christy Spackman

Bibliographic record

VenueCultural Studies Review · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsYork University
Fundersnot available
KeywordsAnthropoceneEnvironmental ethicsAgency (philosophy)SociologyHistorySocial sciencePhilosophy

Abstract

fetched live from OpenAlex

Thinking at the scale of the Anthropocene highlights the significant burden on all life imposed by the residues of industrialization as well as continued pollution. But it also risks a disconnect between the functioning of planetary atmospheres and the functioning of local airs. In this thought-piece, we consider together the potato chip bag, the asthma inhaler, and climate positive building design as scalar practices of Anthropocene air. By figuring Anthropocene air as an interscalar vehicle, we show connections between matter and relations that seem distant and disconnected. We do this by honing in on respiration as a transformative atmospheric process that has been designed in advanced capitalism to extend life for some, while denying life for others. We point to seconds, hours, days, weeks, and seasons to highlight how containment technologies and respiratory processes function in the Anthropocene to remake air. These technologies and practices, which all too often go unnoticed in consumption landscapes, demonstrate that despite Anthropocene air’s tendency to exceed human agency, it is liable to engineering. Doing this offers insight into where different scales of action can be mobilized.

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 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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.524
Threshold uncertainty score0.604

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.063
GPT teacher head0.397
Teacher spread0.334 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreReview

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".

Quick stats

Citations19
Published2019
Admission routes1
Has abstractyes

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