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Record W2055835727 · doi:10.1080/02614367.2010.506647

No more dancing for gods: constructing Taiwanese/Chinese identity through the Ilisin

2011· article· en· W2055835727 on OpenAlexaff
Judy Liao

Bibliographic record

VenueLeisure Studies · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Culture and Media Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsIdentity (music)SociologyGender studiesAestheticsArt

Abstract

fetched live from OpenAlex

In this paper, I examine media narratives of the Ilisin, a touristised indigenous festival in Taiwan. A number of previous studies have examined tourist events and ethnic/racial relations as well as detailed explorations of ethnic relations and dynamic identities in a Taiwanese context. However, through the examination of media narratives of the Ilisin through a Foucauldian lens, I hope to provide a different theoretical conceptualisation of the formation of identities, especially in a Taiwanese setting. In this paper, I analyse 417 articles related to the Ilisin from three newspapers and three magazines between 1996 and 2005 through a Foucauldian discourse analysis. This method enables explorations of discursive practices producing different identity formations. In the end, I illustrate how different identities of ‘us’ versus ‘them’ emerge against the same discursive backdrop. This conclusion argues against a determinist and essentialist view of identity. Hence, it could provide reconsideration towards identity politics, and re‐conceptualisation of the formations and practices of identities.

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 score0.033
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.009
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.083
GPT teacher head0.393
Teacher spread0.310 · 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

Citations5
Published2011
Admission routes1
Has abstractyes

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