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Record W4410177379 · doi:10.1177/23996544251334524

‘A bureaucracy within a bureaucracy’: The Department of Fisheries and Oceans and relationships under the Maa-nulth Treaty

2025· article· en· W4410177379 on OpenAlexafffundabout
Onyx Sloan Morgan

Bibliographic record

VenueEnvironment and Planning C Politics and Space · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicInternational Maritime Law Issues
Canadian institutionsUniversity of VictoriaOkanagan University CollegeUniversity of British Columbia, Okanagan Campus
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsBureaucracyTreatyPolitical sciencePublic administrationFisheryLawBiologyPolitics

Abstract

fetched live from OpenAlex

Despite the acknowledgement of the importance of relations with the ocean for nuučaan̓uł ways of being, relationships between Canada's Department of Fisheries and Oceans (DFO) and nuučaan̓uł Nations remain rife with power inequities. The existence, form, and right for nuučaan̓uł to practice fishing, including commercial fishing, is one such flashpoint where relationships with DFO and thus Canada's policy and general orientation to First Nations are strained. Even for huuʕiiʔatḥ, one of the five First Nations signatories to the Maa-nulth Treaty, coming to the table as equal treaty partners has been difficult due to DFO's orientation to nuučaan̓uł fishing rights, the hierarchy of scientific knowledges, and lack of recognitions of legal authorities through hawiłpatak hawiih. Based on our 10 years of research into the implementation of the Maa-nulth Treaty, in this paper we explore the relationship between Huu-ay-aht First Nations and DFO. To do so, we begin by overviewing the process of reserve creation across nuučaan̓uł ḥaḥuułi and how colonial understandings and creations of 'fisheries' played a key role in dispossession. We then turn to our interviews with Maa-nulth First Nations negotiation and implementation teams to explore how reconciliation and fishing rights have emerged through the Maa-nulth Treaty, and how nuučaan̓uł knowledges have been disregarded by the DFO. We conclude by profiling the tensions, strengths, and challenges huuʕiiʔatḥ have experienced in exercising their treaty rights, inclusive of hawiłpatak hawiih, through the Maa-nulth Treaty and specifically with the Department of Fisheries and Oceans.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.307

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.238
Teacher spread0.224 · 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.

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

Citations0
Published2025
Admission routes3
Has abstractyes

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