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Record W7162103473 · doi:10.82308/32206

The uncanny doubling of sovereign and citizen: anti-state narrativity in Alberta

2020· dissertation· en· W7162103473 on OpenAlexaboutno aff
Vanessa McCuaig

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicLaw in Society and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsSovereigntyState (computer science)UncannyNarrativitySovereign stateState of exceptionAutoethnographyEthnography

Abstract

fetched live from OpenAlex

Over the last decade, Alberta, Canada has been the site of several highly publicized events focused on individuals labelled as “sovereign citizens”. From the occupation of homes and traplines claimed as sovereign territories (CBC 2013a, 2013b) to larger than life court cases with wide public audiences (Meads v. Meads 2012 ABQB 571), sovereign citizens capture the Albertan imagination with their unusual beliefs and practices. Asserting discourses of freedom, liberty, and self-governance, these individuals surface at the junctures of everyday life, challenging state authority through obscure and obtuse interpretations of law. Whether they appear through hegemonic state classificatory schemes used by the media, in stories narrated by Albertans trying to understand the movement, or in legal courts, sovereign citizens are entangled with the worlds they seek to reject. A doubling—the sovereign and the citizen—thus emerges and remerges as individuals challenge the state and its assumed duties, laws, and expectations, all the while they move, transgress, or realign themselves in relationship to the state.Drawing on four months of ethnographic fieldwork between May to September 2018, this thesis thus explores the relationship between sovereign citizens as an elusive and slippery category and Albertans, asking: how do sovereign citizens and Albertan citizens narrate their own (and others’) challenges to the Albertan state

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)0.002
metaresearch head score (Gemma)0.003
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 score0.094
Threshold uncertainty score0.359

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0310.028
Scholarly communication0.0110.002
Open science0.0020.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.017
GPT teacher head0.293
Teacher spread0.276 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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