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Record W3049557064 · doi:10.1139/facets-2020-0004

Sowing a way towards revitalizing Indigenous agriculture: creating meaning from a forum discussion in Saskatchewan, Canada

2020· article· en· W3049557064 on OpenAlexaffvenueabout
Melissa Arcand, Lori Bradford, Dale F. Worme, Graham Strickert, Ken Bear, Anthony Blair Dreaver Johnston, Sheldon M. Wuttunee, Alfred Gamble, Debra Shewfelt

Bibliographic record

VenueFACETS · 2020
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsGlobal Institute for Water SecurityFirst Nations University of CanadaUniversity of Saskatchewan
Fundersnot available
KeywordsIndigenousAgricultureLeaseNegotiationLegislationPolitical scienceLand managementEconomic growthBusinessGeographyEconomicsLawEcology

Abstract

fetched live from OpenAlex

Agriculture is practiced on 3–4 million acres of First Nations reserve lands in the Saskatchewan Prairies—predominantly by non-Indigenous farmers. A confluence of factors including an increase in agricultural land holdings on reserve and greater autonomy in land management have renewed conversations on how First Nations can realize the full economic benefits and exert greater control over agricultural activities that affect the reserve land base. We hosted a Forum on Indigenous Agriculture to share current knowledge on the contemporary status of Indigenous agriculture and to co-formulate research, capacity building, and policy priorities. First Nations’ roles in agriculture are diverse and were categorized in three broad contexts: as farmers, relying on traditional Indigenous or western practice, or a synergy of both; as landlords negotiating lease agreements; and as agribusiness entrepreneurs. Five themes emerged from the forum: centring Indigenous knowledge and traditional relationships to the land, capacity building, building respectful partnerships and relationships, financing farming and equitable economies, and translating research to policy and legislation. The forum provided foundational data to inform research and capacity building to meet community-defined goals in agriculture on reserve lands and by First Nations people.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.303
Teacher spread0.274 · 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 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

Citations19
Published2020
Admission routes3
Has abstractyes

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