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Record W2262273390 · doi:10.1177/1532708615620208

Intimacies of Rock

2015· article· en· W2262273390 on OpenAlexaboutno aff
Bryanne Young

Bibliographic record

VenueCulture Studies &#x2194 Critical Methodologies · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsnot available
Fundersnot available
KeywordsPerformativitySociologyAgency (philosophy)Argument (complex analysis)EthnographyDynamismMeaning (existential)Embodied cognitionEpistemologyAestheticsAnthropologyPhilosophyGender studiesSocial science

Abstract

fetched live from OpenAlex

This essay engages feminist science studies and theories of performativity to inject with dynamism familiar figurations of static being. Through the modalities of ethnographic writing, memory, and embodied experience, I enact a lively engagement with Canada’s Rocky Mountains. By shifting the way we understand this unique, constitutive feature of the Canadian West, I suggest an approach to ethics that expands categories of agency, disaggregating it from realms of human exceptionalism. Through the analytic of performativity, I attend to the dynamic and agentive capacity/ies of glacial bodies, mountains, and lichen—nonhuman bodies considered passive and inert by prevailing epistemologies—to make/materialize meaning. I animate the argument that what we call nature is not a passive, immutable surface on which culture is inscribed, but rather is the production of active, agential practices, each containing divergent wills to power immanent with the capacity to make cuts of their own. The aim of this writing is to think through how mountains, and other such complex living systems, might pose a necessary series of questions to prevailing epistemologies and systems of epistemological capture.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.217
Threshold uncertainty score0.431

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0180.050
Scholarly communication0.0090.005
Open science0.0010.008
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.337
GPT teacher head0.528
Teacher spread0.191 · 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 designQualitative
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

Citations2
Published2015
Admission routes1
Has abstractyes

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