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Record W4386836800 · doi:10.1177/237946152100700210

Institutional Policies for a Healthy Anthropocene Society

2021· article· en· W4386836800 on OpenAlexaff
Andrew J. Hoffman, P. Devereaux Jennings, Nicholas Poggioli

Bibliographic record

VenueBehavioral Science & Policy · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAnthropoceneEpoch (astronomy)Corporate governanceCapitalismEnvironmental ethicsParadigm shiftPolitical scienceSociologyBusinessEconomicsManagementPoliticsEpistemologyLawComputer science

Abstract

fetched live from OpenAlex

The Anthropocene epoch refers to the geological epoch, now underway, that is defined by monumental, human-caused geophysical changes in planetary ecosystems. Human society is also changing, marked by an equally profound shift in attitudes, beliefs, and practices. In this article, we apply research on social change in institutions—that is, in the enduring belief systems, ideas, and practices that guide organizations and society— to propose policies that could prepare Anthropocene society to change in ways that would ensure healthier ecosystems. These policies would alter the institutions driving corporate governance, patterns of consumption, the role of science in business and society, and the time horizons used by governments and organizations to plan, and they would help society adapt to unpredictable changes in the climate and in ecosystems. Ultimately, the policies would shift long-standing institutional structures, or logics, that support market capitalism and the belief in technology's ability to solve all problems to help create a more enlightened culture and more stable ecosystems on a rapidly changing planet.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.845
Threshold uncertainty score0.998

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 studies0.0030.003
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 head0.668
GPT teacher head0.609
Teacher spread0.059 · 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 designNot applicable
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
Published2021
Admission routes1
Has abstractyes

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