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Record W3216450720 · doi:10.1016/j.esg.2021.100122

Reconciling safe planetary targets and planetary justice: Why should social scientists engage with planetary targets?

2021· article· en· W3216450720 on OpenAlex

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 System Governance · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicInnovation, Sustainability, Human-Machine Systems
Canadian institutionsUniversity of Regina
FundersPorticus FoundationGlobal Environment FacilityGordon and Betty Moore Foundation
KeywordsDeliberationEconomic JusticeScholarshipPlanetary boundariesEnvironmental ethicsSocial justiceHumanityPolitical scienceSet (abstract data type)AstrobiologySociologyBiologyLawComputer scienceSustainable development

Abstract

fetched live from OpenAlex

As human activity threatens to make the planet unsafe for humanity and other life forms, scholars are identifying planetary targets set at a safe distance from biophysical thresholds beyond which critical Earth systems may collapse. Yet despite the profound implications that both meeting and transgressing such targets may have for human wellbeing, including the potential for negative trade-offs, there is limited social science analysis that systematically considers the justice dimensions of such targets. Here we assess a range of views on planetary justice and present three arguments associated with why social scientists should engage with the scholarship on safe targets. We argue that complementing safe targets with just targets offers a fruitful approach for considering synergies and trade-offs between environmental and social aspirations and can inform inclusive deliberation on these important issues.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.413
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.276
Teacher spread0.251 · 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