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Record W4413874164 · doi:10.1080/17449855.2025.2532678

Canada’s dual and antithetical roles: An interview with Kit Dobson about <i>We Are Already Ghosts</i>

2025· article· en· W4413874164 on OpenAlexaboutno aff
Rocío Carrasco Carrasco, Irene López Rodríguez

Bibliographic record

VenueJournal of Postcolonial Writing · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicPhilippine History and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsDual (grammatical number)HistoryArtLiterature

Abstract

fetched live from OpenAlex

Kit Dobson’s work focuses on several controversial issues in Canadian Indigenous history. The effects of oil capitalism on the environment is at the core of Field Notes on Listening, while Malled: Deciphering Shopping in Canada addresses the socio-economic impacts of shopping malls in Canada. Transnational Canadas: Anglo-Canadian Literature and Globalization examines Canadian literary traditions in the context of globalization, and We Are Already Ghosts tackles issues of Indigenous identities and the current politics surrounding the Truth and Reconciliation Commission. All these, and Dobson’s edited works – Please, No More Poetry: The Poetry of derek beaulieu; Producing Canadian Literature: Authors Speak on the Literary Marketplace; Transnationalism, Activism, Art; Dissonant Methods: Undoing Discipline in the Humanities Classroom; and All the Feels: Affect and Writings in Canada – serve as a springboard for this interview in tracing his diverse viewpoints about Canada’s evolution from a colonial past.

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)0.003
metaresearch head score (Gemma)0.008
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: Other · Consensus signal: none
Teacher disagreement score0.097
Threshold uncertainty score0.704

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0730.018
Scholarly communication0.0100.003
Open science0.0020.003
Research integrity0.0050.010
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 head0.013
GPT teacher head0.284
Teacher spread0.272 · 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
GenreOther

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 routes1
Has abstractyes

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