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Record W4362566769 · doi:10.1002/symb.641

Wild Lives

2023· article· en· W4362566769 on OpenAlexaboutno aff
Lindsay Hamilton

Bibliographic record

VenueSymbolic Interaction · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsHumanismSociologyPower (physics)StupidityCitationArt historyMedia studiesHistoryPhilosophyTheologyLawPolitical sciencePsychology

Abstract

fetched live from OpenAlex

On a typical day, rising at dawn, I slip my old coat over my pajamas to stand in the backyard.Through a coil of coffee-steam, I watch the pigeons rustle in the damson tree or crouch to examine things at soil-level; a leaf, a paw-print.Sometimes, I slip through the back gate and let my eyes settle on a point in the distance, past the bronze sandstone of the ancient church steeple that bisects the fields, tall trees and hedgerows.A curl of smoke will be rising, reliably, from the chimney-pot of the solitary cottage in the hazy far distance.My terrier has his snub black nose to the ground, reading last night's news.These are the primary moments of my day-to-day experience of the place where I live, a quiet and unpopulated part of the country that may, at first sight look empty but one which positively hums with life.Of course, human notions of what constitutes a civilization, and conversely, a wilderness differ immensely, as do our relative attachments to the varied land and cityscapes that make up our concept of home.Over several decades of fieldwork, Strathern (2023), for example, has shown how embodied experiences of place are messily entangled with relative notions of culture, kinship, language and knowledge; those negotiated "fields of power" that Ingold (2021) describes as a "dwelling perspective."So, what does it really mean to live somewhere, to "inhabit" a place?How best to consider the relations between humans and other actors in their lifeworlds?How can we understand belonging, particularly in "unpopulated" areas which bear so few traces of human dwelling and activity?These questions are raised within the context of the Canadian wilderness in Phillip and April Vannini's path-breaking anthropological book (and film) that draws on the variegated legacy of inhabitation scholarship, if it is possible to group it together thus,

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)0.003
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 score0.373
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.002
Scholarly communication0.0070.006
Open science0.0020.008
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.3730.174

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 head0.036
GPT teacher head0.364
Teacher spread0.328 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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