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Record W4403947171 · doi:10.1002/eas2.12019

A heart model of <i>Earth Stewardship</i>

2024· article· en· W4403947171 on OpenAlex
Marten Scheffer, John M. Anderies, Tone K. Bjordam, Johan Bollen, Stephen R. Carpenter, F. Stuart Chapin, Carl Folke, Francisco Gazitua, Milena Holmgren, Jorge Marcone, Steve Polasky, Elke U. Weber, Frances Westley

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEarth stewardship. · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsStewardship (theology)Earth (classical element)Environmental sciencePolitical scienceMathematicsMathematical physics

Abstract

fetched live from OpenAlex

Abstract Few disagree that we should pass on the Earth in good shape to future generations, and many scientists want their work to contribute to that goal. Recent work has shown that hopelessness stands in the way of people taking an active attitude. At the same time, it is becoming clear what can be done about that: providing compelling visions of attractive futures and highlighting feasible pathways. Currently, science and the humanities are not well designed for this task. Practices that stand in the way of a more holistic change‐making approach include proposal‐based funding, paralyzing rigor requirements, and a focus on explanation rather than action. Removing those barriers may require culture shifts, a notoriously difficult and slow kind of change. Meanwhile, realistic inspiring future scenarios can be developed by bringing diverse thinkers together in environments where time, space, and immediate outcomes are not pressing.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.927
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.313
GPT teacher head0.416
Teacher spread0.103 · 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