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Record W4388894149 · doi:10.1111/sjtg.12518

A train reaction: the infrastructural politics and mobility injustices accompanying Hanoi's new urban railway Line <scp>2A</scp>

2023· article· en· W4388894149 on OpenAlexaff
Sarah Turner, Binh N. Nguyen, Madeleine Hykes

Bibliographic record

VenueSingapore Journal of Tropical Geography · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicWater Governance and Infrastructure
Canadian institutionsMcGill University
Fundersnot available
KeywordsVietnamesePoliticsLivelihoodHo chi minhCapital (architecture)ReputationCapital cityBusinessEconomic growthPolitical scienceGeographySociologySocioeconomicsEconomicsEconomic geographyLawArchaeology

Abstract

fetched live from OpenAlex

In 2008, Vietnam's Prime Minister approved the construction of the ‘Hanoi Urban Railway System’, a major infrastructure project for the country's capital city. The construction of Line 2A, the first line of this 8‐line railway, took ten years to complete, and was finally inaugurated in November 2021. Spanning 13 km across the city centre, Line 2A encountered more than just construction setbacks, with its reputation tarnished by contractor choice, accidents, and public scepticism over safety and accessibility. Sowing further seeds of doubt in the minds of many Hanoi residents is the fact that two‐thirds of the original financing came from preferential loans from Vietnam's large northern neighbour, conditional on the contractor and key materials being sourced from Vietnam's large, northern neighbour. Moreover, the project is informally categorized as part of Vietnam's large northern neighbour's Belt and Road Initiative. Drawing from conceptual literature regarding infrastructural politics and mobility (in)justice, we analyse how Hanoi residents have experienced and negotiated the construction of this Chinese‐Vietnamese infrastructure project. In particular, we consider how the livelihoods of those directly affected by the railway's operations, namely motorbike taxi‐drivers, have been impacted to date.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.562

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.018
GPT teacher head0.278
Teacher spread0.260 · 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 designObservational
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

Citations12
Published2023
Admission routes1
Has abstractyes

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