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Record W3005091740 · doi:10.1163/24688800-00301009

Destabilising Empires from the Margin: Report of the 25th North American Taiwan Studies Association Annual Conference, Seattle, 16–18 May 2019

2020· article· en· W3005091740 on OpenAlexaff
Szu-Yun Hsu, Agnes Ling-Yu Hsiao

Bibliographic record

VenueInternational Journal of Taiwan Studies · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicHong Kong and Taiwan Politics
Canadian institutionsMcMaster University
Fundersnot available
KeywordsEmpireDemocratizationAsian studiesConversationPoliticsPolitical scienceFace (sociological concept)Media studiesHistorySociologyGender studiesChinaLawSocial scienceDemocracy

Abstract

fetched live from OpenAlex

Abstract The 25th natsa post-conference report documents the initiation, organisation, and proceedings of the event, followed by some general reflections on what we can further investigate in the future. This year, we invited scholars worldwide to come together and rethink and offer critiques on the possibilities and challenges facing Taiwan studies by unpacking the idea of ‘empire’ and ‘marginality’. Given that agenda, we opened up discussions on some key topics around researching Taiwan and East Asia, such as political economy, democratisation, transitional justice, reconciliation, lgbtq, and culture studies. Attempting to reposition Taiwan studies in the broader intellectual terrain, a series of insightful dialogues thus emerged, pointing out alternatives of Taiwan studies in the face of empire(s) and marginality. In all, the natsa has formed one of the most widely known and vivid platforms for intellectual exchanges on Taiwan studies and further conversation shall continue alongside the growth of the scholarly community.

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)0.004
metaresearch head score (Gemma)0.004
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.041
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0060.002
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0180.001

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 head0.074
GPT teacher head0.378
Teacher spread0.304 · 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
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

Citations1
Published2020
Admission routes1
Has abstractyes

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