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Record W3161425117 · doi:10.15353/cfs-rcea.v8i1.494

Review of "Thinking with soils: Material politics and social theory"

2021· article· en· W3161425117 on OpenAlexaffvenue
Kaitlyn Duthie-Kannikkatt

Bibliographic record

VenueCanadian Food Studies / La Revue canadienne des études sur l alimentation · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsPoliticsFace (sociological concept)Embodied cognitionSociologyNarrativeSet (abstract data type)Environmental ethicsCritical reflectionEpistemologySocial sciencePolitical sciencePedagogyPhilosophy

Abstract

fetched live from OpenAlex

Drawing on the pioneering work of Maria Puig de la Bellacasa, the contributors to Thinking with Soils: Material Politics and Social Theory argue that it is time for social scientists to deepen our own understanding of soil. We need to consider how to think with soils and recentre the set of embodied relationships that lie at the heart of this lively world beneath our feet. The only way to confront the ecological crisis we face is to decolonize our narratives of conservation and reimagine it as an ongoing process of socioecological entanglement in which humans and non-humans are active agents. The collection succeeds in prompting deep and meaningful consideration of what it might mean to live into our relationships with soil, and how sustained reflection on the material politics of soil might shift the way we think about and act on the so-called soil crisis.

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)0.004
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.087
Threshold uncertainty score0.174

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0080.017
Science and technology studies0.0030.011
Scholarly communication0.0060.006
Open science0.0030.003
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0050.002

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 head0.045
GPT teacher head0.301
Teacher spread0.256 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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 routes2
Has abstractyes

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