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Record W4283757739 · doi:10.3390/socsci11070286

Precursors and Antecedents of the Anthropocene

2022· article· en· W4283757739 on OpenAlexaff
Thomás Heyd

Bibliographic record

VenueSocial Sciences · 2022
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy and Sustainability Research
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsAnthropoceneEpoch (astronomy)Earth system scienceEnvironmental ethicsPerspective (graphical)PoliticsHistoryIndustrial RevolutionScale (ratio)PrehistoryEpistemologyGeographyEcologyPolitical scienceArchaeologyComputer sciencePhilosophyBiologyLawCartography

Abstract

fetched live from OpenAlex

There seem to be two sorts of debates about precursors and antecedents to the Anthropocene. One concerns the question whether the concept of the Anthropocene was captured by earlier terms, such as “noösphere” or “the Anthropozoic Era”. The other concerns whether the full-scale transformation of Earth systems was already, at least partially, triggered sometime prior to the 19th century Industrial Revolution. This paper takes a wider perspective, which may be seen as orthogonal to these debates, by enquiring whether there are other biological agents in Earth history who may have generated a new Epoch, and also by seeking to identify historical and prehistoric antecedents in human–nature relations that may foreshadow the Anthropocene. One conclusion is that humans are certainly not the first biotic agents becoming drivers of planetary system changes. Another conclusion, ironically, is that some cultural innovations that were adaptive under earlier conditions presently have become collectively mal-adaptive and contributory to the hazards of our new Epoch. Finally, it is suggested that while it may be unclear whether we can manage the socio-political challenges of our times, our adaptive versatility in principle ought to suffice to successfully manage the climate challenges of the Anthropocene.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.277
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.025
GPT teacher head0.330
Teacher spread0.305 · 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.

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

Citations2
Published2022
Admission routes1
Has abstractyes

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