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Record W3191108347 · doi:10.15273/jue.v11i2.11037

The Temporality of Identity in Planned Cities: A Case Study of Zhong Xing New Village, Taiwan

2021· article· en· W3191108347 on OpenAlexvenueno aff
Michelle Lu

Bibliographic record

VenueJournal for Undergraduate Ethnography · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicHong Kong and Taiwan Politics
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsHegemonyPopulationAuthoritarianismNationalismPolitical scienceEconomic growthNational identityGovernment (linguistics)SociologyDemocracyLawEconomicsDemography

Abstract

fetched live from OpenAlex

In 1957, the Kuomintang (KMT), Chiang Kai-Shek’s nationalist government, planned and built Zhong Xing New Village (ZXNV), a garden city, to house the Taiwan Provincial Government. Despite the benefits of public housing, healthcare, and education, ZXNV experienced a two-third drop in population after 1985. The political liberalization and democratization of Taiwan in the 1980s and 1990s led to the reclamation of Taiwanese national identity that rejected the hegemony of the KMT and the physical manifestations of this colonial history, including ZXNV. ZXNV was a utopian ideal constructed during a time of authoritarian rule for a specific political purpose and homogenous population. ZXNV’s inability to change its purpose and identity led to its ultimate depopulation. Ethnographic fieldwork reveals the changes in ZXNV’s built environment and neighborhood culture influenced by socio-political transformations over the last sixty years. Fourteen interviews were conducted with two generations of ZXNV residents, and archival research reveals the intended design and policies of the city. Key findings include the structural flaws in the city’s design, the exposure of political tensions between the national and provincial governments, and the changing national identity of Taiwan due to globalization, all of which led to the ultimate downfall of Zhong Xing New Village.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.528
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.071
GPT teacher head0.398
Teacher spread0.327 · 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 teacher head, 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

Citations0
Published2021
Admission routes1
Has abstractyes

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