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Record W3015146104 · doi:10.1080/2373566x.2020.1717979

What Could Wild Life Be? Etho-ethnographic Fables on Human-Animal Kinship

2020· article· en· W3015146104 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueGeoHumanities · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsRoyal Roads University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsEthnographyHumanityKinshipNational parkIndigenousAutonomyPerspective (graphical)AnthropologySociologyEnvironmental ethicsEthnologyAestheticsGeographyEcologyBiologyArtPolitical scienceArchaeologyVisual artsPhilosophy

Abstract

fetched live from OpenAlex

Can humans and wild life co-exist? Drawing from ethnographic fieldwork conducted in and nearby Waterton Lakes National Park and Banff National Park, Alberta, Canada, we present two etho-ethnographic fables that show how a positive coexistence of humans and wild life may be sought after and achieved. The two stories–narrated by animals’ voices–prompt us to rethink the very meanings of wild life and humanity and challenge us to envision and appreciate a new kind of affective relationship between people and non-human animals. By attending to the mutual trust and care inherent in respect-based multi-species entanglements, in this article we attune ourselves to the importance of the relational autonomy of wild animals and generate ideas on what wild life could be when understood from the perspective of relational and Indigenous ontologies.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.763
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0010.000
Research integrity0.0000.001
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 head0.201
GPT teacher head0.381
Teacher spread0.180 · 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