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Record W6994641707

9781529235319.pdf

2024· other· en· W6994641707 on OpenAlexaboutno aff

Bibliographic record

VenueOAPEN (The OAPEN Foundation) · 2024
Typeother
Languageen
FieldNursing
TopicBiochemical Analysis and Sensing Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsClimate justiceGrassrootsScholarshipFace (sociological concept)PoliticsEconomic JusticeEcofeminismClimate change
DOInot available

Abstract

fetched live from OpenAlex

Available open access digitally under CC-BY-NC-ND licence. Bringing together interdisciplinary climate change scholarship and grassroots activism, this book considers the possibilities of planetary justice across human difference, generations, species and the concept of life and non-life. Writing amidst bushfires, cyclones, global climate strikes and a global pandemic, contributors from the Earth Unbound Collective share stories from India, Australia, Canada and Scotland. Chapters draw on Indigenous, Black, Southern, ecosocialist and ecofeminist perspectives to call for more radical and interconnected ideas of justice and solidarity. This accessible book features diverse voices that speak with the planet in the face of climate change, biodiversity loss and extinction. It explores the politics and practices of working towards a future where the planet thrives.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.077
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0080.004
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.9230.904

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 head0.013
GPT teacher head0.277
Teacher spread0.264 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2024
Admission routes1
Has abstractyes

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