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Record W1503325695

"Struggle Work": Global and Urban Citizenship in Dionne Brand’s What We All Long For

2006· article· en· W1503325695 on OpenAlexaffvenueabout
Kit Dobson

Bibliographic record

VenueStudies in Canadian Literature · 2006
Typearticle
Languageen
FieldArts and Humanities
TopicShort Stories in Global Literature
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsAllegiancePoliticsCitizenshipSociologySpace (punctuation)Resistance (ecology)Gender studiesConstruct (python library)AestheticsPolitical scienceLawArtPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Dionne Brand's 2005 novel What We All Long For represents a generational shift in the politics of being in Canadian space. In it, young, poor, and racialized characters navigate their lives and loves within the urban space of the Greater Toronto Area. Instead of pledging allegiance to the nation-state or longing for a lost home, drifting between or beyond such positions makes possible a new and liberating politics. Brand pursues a rhizomatic form of political resistance in her writing, in which one point can connect to any other to form communities. Old notions of grounded selfhood and belonging are necessarily disrupted in order to uncover a site for being that is open, neither nostalgic nor caught within the politics of inclusion/exclusion or an inside/outside dichotomy. Brand's deterritorializing project is importantly focused upon urban modes of being that constantly elude the dominant. The novel demonstrates this point in focusing upon protagonists who work actively to construct a new Toronto from below, but whose relatives and friends are caught within a racist system that seeks to limit how their bodies and beings might function.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.228
Threshold uncertainty score0.458

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0390.056
Scholarly communication0.0140.005
Open science0.0010.007
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.000

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 head0.027
GPT teacher head0.270
Teacher spread0.243 · 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 designNot applicable
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

Citations13
Published2006
Admission routes3
Has abstractyes

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