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Record W2761623771 · doi:10.1111/anti.12362

Environmentality on the Canadian Prairies: Settler‐Farmer Subjectivities and Agri‐Environmental Objects

2017· article· en· W2761623771 on OpenAlexaffabout
Julia M.L. Laforge, Stéphane M. McLachlan

Bibliographic record

VenueAntipode · 2017
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsIndigenousAgricultureState (computer science)ColonialismResistance (ecology)NarrativeGeographyPolitical scienceSociologyEcologyArchaeology

Abstract

fetched live from OpenAlex

Abstract State and institutional actors have been shaping settler‐farmer subjectivities in order to transform the landscape and thus the history and geography of the Canadian Prairies. This paper expands the application of environmentality from its origins in colonial forestry to interrogate agriculture on prairie landscapes. The Canadian state used the technologies of environmentality to influence “common sense” attitudes and behaviours, which acted to deterritorialize Indigenous communities and then manipulated their subjectivities to guarantee settler‐farmer access to land. Later, institutions and states moulded settler‐farmer subjectivities of correct farming behaviour in an effort to convert soil, water, and seeds into economic resources. These environmental objects, in turn, acted upon settler‐farmer subjects by setting biophysical and genetic limits such as soil fertility, water quality and quantity, and plant hardiness and disease resistance. Resisting environmentality requires understanding processes of subjugation while also creating counter‐narratives of “good” farming behaviour and Indigenous‐settler relations.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.598
Threshold uncertainty score0.978

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 studies0.0230.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.044
GPT teacher head0.335
Teacher spread0.291 · 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 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

Citations20
Published2017
Admission routes2
Has abstractyes

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