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Record W2921066042 · doi:10.3390/soc9010021

The Sedanthropocene: Nomadism, Ecology, Hypernormalization: Toward Reimagining the Holocene

2019· article· en· W2921066042 on OpenAlexaff
David Selsky

Bibliographic record

VenueSocieties · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Geoengineering
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAnthropoceneDualismCapitalismCITESSociologyEnvironmental ethicsHoloceneCapital (architecture)EcologyHistoryEpistemologyPhilosophyPolitical scienceArchaeologyBiologyLaw

Abstract

fetched live from OpenAlex

The various (s)cenes of Anthropocene discourse are attempts to conceptualize the problem of anthropogenic global warming and to better understand the problem with a view to possible solutions. This paper explores, in a series of theoretic vignettes, ways that these attempts are too myopic and narrow, and tend to ignore the possibility that the most fundamental levels of social organization might be the very conditions under which other ‘cenes’ can function at all. Specifically, Jason Moore’s Capitalocene describes and explains many symptoms of a world enraptured by capital. However, the beginning of the Holocene marks an historical stage wherein humans changed their thoughts and behaviours in such a way as to make something like capitalism possible at all. The dualism that Moore cites as fundamental to the Capitalocene did not begin with Descartes, it began with anatomically modern humans circa 10,000 years ago.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.036
Scholarly communication0.0040.008
Open science0.0000.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.217
Teacher spread0.207 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations0
Published2019
Admission routes1
Has abstractyes

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