MétaCan
Menu
Back to cohort
Record W1965852825 · doi:10.5038/2162-4593.12.1.2

Landscape Aesthetics, Water, and Settler Colonialism in the Okanagan Valley of British Columbia

2008· article· en· W1965852825 on OpenAlexaffabout
John Wagner

Bibliographic record

VenueJournal of Ecological Anthropology · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsUniversity of the Fraser ValleyUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsColonialismIndigenousSettlement (finance)TourismGeographyAgricultureCultural landscapeHistoryArchaeologyEcology

Abstract

fetched live from OpenAlex

Historic and contemporary patterns of settler colonialism and agricultural development in the Okanagan Valley of British Columbia are described, emphasizing the ways in which settler culture has led to the production of a landscape aesthetic that reproduces colonization as an iterative cultural practice. I explore the ways in which this particular landscape aesthetic is dependent on the economic and symbolic meanings of water in Okanagan settlement history. The images of the Okanagan that were used to attract settlers to the valley a century ago emphasized the lush, oasis-like qualities of orchards and lakes set among a dramatic, arid and mountainous backdrop. This oasis aesthetic exists in sharp contrast to that held by the Syilx indigenous people who were displaced and marginalized as a consequence of agricultural development. Today, as land prices escalate and orchards become less economically viable, it is the orchardists themselves who are being displaced by a new generation of settlers who come here to retire or make their livings in the wine tourism industry. As the environmental costs of these changes accumulate, Okanagan residents are challenged to articulate a more sustainable landscape aesthetic rooted in local ecology.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0100.005
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.028
GPT teacher head0.307
Teacher spread0.279 · 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

Citations15
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Ecological AnthropologySame topicGeographies of human-animal interactionsFrench-language works237,207