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Canadian Human Landscape Examples

2006· article· en· W1484546384 on OpenAlexaffvenueabout
Bonnie C. Hallman, S. Mary P. Benbow

Bibliographic record

VenueCanadian Geographies / Géographies canadiennes · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsInscribed figureCultural landscapePresentation (obstetrics)Context (archaeology)GeographyPlan (archaeology)SociologyEthnologyEnvironmental ethicsAnthropologyHistoryArchaeology

Abstract

fetched live from OpenAlex

In this paper, we initiate a discussion of zoos as cultural landscapes, using the example of the Assiniboine Park Zoo in Winnipeg, Manitoba. We start from the notion that zoos are cultural institutions that do not reflect nature itself but are created landscapes inscribed with social and cultural messages conveyed through the presentation of wild animals. We examine the development of this zoo in the context of the stages through which it has passed in its over a hundred years of existence on the basis of historical accounts as well as Assiniboine Park Zoo master plan and annual report documents. We argue for examining zoos as cultural landscapes that reflect the changing relations between humans and animals and with ‘nature’ more generally.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.031
Threshold uncertainty score0.224

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.008
Science and technology studies0.0130.004
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0160.001

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 head0.014
GPT teacher head0.241
Teacher spread0.227 · 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 designObservational
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

Citations21
Published2006
Admission routes3
Has abstractyes

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