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Record W4214878814 · doi:10.1177/14634996211067307

The misperception of the environment: A critical evaluation of the work of Tim Ingold and an alternative guide to the use of the senses in anthropological theory

2022· article· en· W4214878814 on OpenAlexaff
David Howes

Bibliographic record

VenueAnthropological Theory · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsConcordia University
Fundersnot available
KeywordsSocialitySociologyPerceptionEthnographyAestheticsEpistemologyAttunementCritical theoryNoveltyOmnipresenceMediationSocial anthropologyCritical thoughtCulture theoryAnthropologySocial psychologyPsychologySocial sciencePhilosophy

Abstract

fetched live from OpenAlex

This article presents a critical evaluation of the work of Tim Ingold from the standpoint of social and sensory anthropology. It acknowledges the novelty of the emphasis on enskillment, movement, process, and growth in Ingold's work. However, it is critical of his abstraction of the senses, which are rendered ‘interchangeable’, and of persons, who are reduced to generic individuals. Ingold's anthropology is shown to be pre-cultural and post-social at once, with the result that it fails to address the sociality of sensation and cultural mediation of perception. Ingold's doctrine of ‘direct perception’ is exposed as particularly problematic. In place of his emphasis on ‘the life of lines’, this article foregrounds the life of the senses, and in lieu of his diminution of the social, it acknowledges the politics of perception that inform most every perceptual act. The article concludes with a series of reflections on how to go about sensualizing anthropological theory and practicing sensory ethnography (i.e. the methodology of participant sensation).

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)0.042
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.042
Threshold uncertainty score0.220

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0420.042
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0090.004
Science and technology studies0.0230.103
Scholarly communication0.0160.023
Open science0.0040.010
Research integrity0.0080.011
Insufficient payload (model declined to judge)0.0030.000

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 head0.107
GPT teacher head0.420
Teacher spread0.313 · 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 designTheoretical or conceptual
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

Citations37
Published2022
Admission routes1
Has abstractyes

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