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Record W4232894622 · doi:10.3138/9781442679221-fm

Frontmatter

2001· book-chapter· en· W4232894622 on OpenAlexaff
Annabelle Sabloff

Bibliographic record

VenueUniversity of Toronto Press eBooks · 2001
Typebook-chapter
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsYork University
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Reordering the Natural World is a fascinating account of the many and varied ways in which animals and humans interact in the urban context.In looking at these interactions, Annabelle Sabloff argues that the everyday practices of contemporary capitalist society contribute to our alienation from the rest of nature.At the same time, however, she reveals the often disguised affinities and sense of connection that urban Canadians nonetheless manifest in their relations with animals and the natural world.Sabloff reflects on how the discipline of anthropology has contributed to the prevailing Western perception of a divide between nature and culture.She suggests that the present ecological crisis has resulted largely from the ways in which Western societies have construed nature as a cultural system.Since new ideas about nature may be critical in changing humanity's destructive interactions with the biosphere, Reordering the Natural World is invaluable in exploring how urban Canadians develop and sustain their current relationship with the macrocosm, and in considering whether these relationships might be altered by reconceptualizing anthropology itself as an integral part of natural history.With this unique text, Sabloff not only provides provocative insight into the study of relations between humans and the natural world, she lays a cornerstone for building a new structure for the study of anthropology itself.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.163
Threshold uncertainty score0.233

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.8370.644

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 head0.031
GPT teacher head0.255
Teacher spread0.224 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueUniversity of Toronto Press eBooksSame topicGeographies of human-animal interactionsFrench-language works237,207