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Record W2078804376 · doi:10.1353/tech.2011.0148

Technology, Bodily Limits, and Ways of Knowing: Joy Parr Sensing Changes

2011· article· en· W2078804376 on OpenAlexaboutno aff
Shannon Jackson

Bibliographic record

VenueTechnology and Culture · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsnot available
Fundersnot available
KeywordsSentienceSituatedEthnographySociologyNatural (archaeology)AestheticsSustainabilityField (mathematics)Environmental ethicsEpistemologyFunction (biology)AnthropologyPhilosophyEcologyHistoryComputer scienceArchaeology

Abstract

fetched live from OpenAlex

This analysis of Joy Parr’s Sensing Changes (2010) connects the central themes of her historical and ethnographic accounts of megaprojects in Canada to broader arguments about the relationship between historically situated bodies and technologies. Much of what is being traced in her case studies is a very local reckoning of how bodies create, employ, and transmit expertise about landscape, be it natural or cultural or both. Her emphasis on the local and her use of ethnography draws the theoretical field of vision downward, challenging both the academic view from nowhere. Agents “on the ground” engaging in everyday activity provide vital clues to the way our bodies function as instruments of knowledge; how the points of contact between sentience and material limit yield social boundaries that are flexible and morally responsive offers an instructive contrast to systems that challenge or transcend such points of contact and threaten sustainability.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.988
Threshold uncertainty score0.306

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0120.056
Scholarly communication0.0130.013
Open science0.0020.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.051
GPT teacher head0.287
Teacher spread0.236 · 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.

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

Citations1
Published2011
Admission routes1
Has abstractyes

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