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Record W4408110024 · doi:10.1080/01436597.2025.2467397

From ghost projects to grassroots future: the Gwadar Haq Do Tehreek and reclamation of failed development in Gwadar, Balochistan

2025· article· en· W4408110024 on OpenAlexaff
Bakhtawer Nawaz Khan, Noor Bakhsh

Bibliographic record

VenueThird World Quarterly · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicWater Governance and Infrastructure
Canadian institutionsYork University
Fundersnot available
KeywordsGrassrootsLand reclamationPolitical scienceEconomic growthGeographyArchaeologyPoliticsEconomicsLaw

Abstract

fetched live from OpenAlex

In this paper, we delve into the lingering spectral presences resulting from the failed China Pakistan Economic Corridor (CPEC) infrastructural endeavour in Gwadar, Balochistan. We focus specifically on the dynamics of the Gwadar Haq Do Tehreek (HDT) social movement that arose in response. Predominantly, our examination sheds light on the profound dissatisfaction of Gwadar’s fishermen, members of the Baloch nation who constitute over 70% of Gwadar’s populace. We move beyond the description of CPEC’s failure by proposing that the project, while a failed venture in terms of development for Balochistan’s inhabitants, paradoxically catalysed resistance movements to fight the ghostly remnants of such infrastructural endeavours. These movements not only brought attention to the fishermen’s plight but also underscored the historical injustices inflicted upon the land- and sea-scape of Balochistan by the state of Pakistan. Moreover, we illustrate how the local community has repurposed the unsuccessful CPEC’s infrastructure for their future-­making, primarily through HDT. Through critical development theories, infrastructural studies, and future studies, our analysis highlights the nuanced understanding of infrastructural development among marginalised native communities in postcolonial South Asia, focusing on Baloch of Balochistan.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.598
Threshold uncertainty score0.895

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.007
GPT teacher head0.257
Teacher spread0.251 · 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

Citations6
Published2025
Admission routes1
Has abstractyes

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