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Record W2955560257 · doi:10.1080/14649373.2019.1614731

Routed through Canada: a roundtable discussion on Inter-Asia and transnational research

2019· article· en· W2955560257 on OpenAlexaffabout
Helen Hok‐Sze Leung, Y‐Dang Troeung, Robert Diaz, Lara Campbell

Bibliographic record

VenueInter-Asia Cultural Studies · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversity of TorontoWomen's and Gender Studies et Recherches FéministesUniversity of British ColumbiaSimon Fraser University
Fundersnot available
KeywordsDiasporaGlobalizationGender studiesChinaPolitical scienceFraternitySociologyMedia studiesHistoryLaw

Abstract

fetched live from OpenAlex

The series of reflections are based on a roundtable discussion amongst Canada-based scholars with research interest in transnational, postcolonial, migration and diaspora studies. Their reflections engage with key ideas from Inter-Asia Cultural Studies through the lens of their research practices and personal histories. Y-Dang Troeung revisits generational memories that are shaped by the “Cold War fraternity” of China, Cambodia, and North Korea through the perspective of Critical Refugee Studies and her personal transits between Asia and Canada. Robert Diaz traces shifts in migratory routes by attending to diasporic returns to the Philippines under complex conditions of globalization that shape and constrain mobility between North America and Asia. Lara Campbell examines overlooked moments of transpacific connections in Canadian women’s history to show how Inter-Asia encounters complicated the racial dynamics of the suffrage movement in early twentieth century British Columbia. The roundtable discussion demonstrates the potential for ongoing dialogues on Inter-Asia issues among scholars in Canada and beyond.

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)0.014
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.882
Threshold uncertainty score0.878

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.018
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.006
Science and technology studies0.1180.032
Scholarly communication0.0240.008
Open science0.0080.014
Research integrity0.0220.034
Insufficient payload (model declined to judge)0.0090.001

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 head0.089
GPT teacher head0.368
Teacher spread0.279 · 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.

Study designNot applicable
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
Published2019
Admission routes2
Has abstractyes

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