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Record W7024201596

The Return of the ‘Children of Nature’: Spectacle and Environment during Banff's Indian Days

2011· other· en· W7024201596 on OpenAlexaboutno aff

Bibliographic record

VenueBulletin of Miscellaneous Information (Royal Gardens Kew) · 2011
Typeother
Languageen
FieldMathematics
TopicTensor decomposition and applications
Canadian institutionsnot available
Fundersnot available
KeywordsSpectacleIndigenousPopulationInterpretation (philosophy)The artsMetis
DOInot available

Abstract

fetched live from OpenAlex

Cross-Pollinations Workshop Presentations 2011 NiCHE has archived 17 audio presentations from this event This collaborative and interdisciplinary workshop brought together Canadian experts (historians, writers, literary critics, curators, environmental consultants, and visual artists) in the production and interpretation of text and visual imagery to better understand how such media enable us to know and then act on behalf of places in more sustainable and ethical ways. The places in question are Western Canadian places, including desert, prairie, mountain, and coastal environments. Citation Jonathan Clapperton “The Return of the ‘Children of Nature’: Spectacle and Environment during Banff's Indian Days” Cross-Pollination: Seeding New Ground for Environmental Thought and Activism across the Arts and Humanities. 25 March 2011. Bio : Clapperton is a PhD Candidate in the Department of History, University of Saskatchewan. Abstract : Though the indigenous population was largely excluded from Banff National Park after its creation, they would return en masse once a year for the Banff Indian Days. This paper explores how both Natives and non-Natives attempted to "restore" Aboriginal peoples to the park. It also sheds light on the various tensions that resulted from the agendas of participants, organizers and spectators, tensions which would ultimately result in conflict and the Indian Days' demise.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.037
Threshold uncertainty score0.964

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0370.000

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 head0.005
GPT teacher head0.184
Teacher spread0.179 · 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 teacher head, not a consensus.

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
Published2011
Admission routes1
Has abstractyes

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