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Record W2781572297 · doi:10.1111/1600-0498.12149

Survival Science: Crisis Disciplines and the Shock of the Environment in the 1970s1

2017· article· en· W2781572297 on OpenAlexaff
Michael Egan

Bibliographic record

VenueCentaurus · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicAmerican Environmental and Regional History
Canadian institutionsMcMaster University
Fundersnot available
KeywordsEnvironmental crisisReactionaryEcological crisisEnvironmental ethicsEpistemologyPoliticsIntuitionDisciplineSociologySocial sciencePolitical scienceLawPhilosophy

Abstract

fetched live from OpenAlex

The 1970s mark a critical departure point in the history of science. The rise of the environmental crisis prompted not just new avenues of scientific inquiry but also the integration of scientific expertise into complex interactions with politics and society. This paper investigates the history of the new ‘crisis disciplines’ that emerged in response to explicit fears that the world was on the verge of ecological collapse. Crisis disciplines – a term coined by the conservation biologist Michael Soulé – engage in the urgent and reactionary pursuit of solutions to pressing environmental problems and the evidence scientists bring to bear on their work. Crisis disciplines involve acting ‘before knowing all the facts’, and therefore constitute ‘a mixture of science and art, and their pursuit requires intuition as well as information’. Combined, diverse crisis disciplines constitute a new kind of ‘survival science’, which emerged in the 1970s.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.994
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.032
Scholarly communication0.0060.008
Open science0.0010.004
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0050.001

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 head0.011
GPT teacher head0.223
Teacher spread0.213 · 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.

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

Citations22
Published2017
Admission routes1
Has abstractyes

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