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Record W2321495659 · doi:10.1177/0973174114567367

Governing Growth

2015· article· en· W2321495659 on OpenAlex
Daniel M. Sabet, Afsana Tazreen

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of South Asian Development · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicBangladesh Politics, Society, and Development
Canadian institutionsImpact
Fundersnot available
KeywordsLegislationGovernment (linguistics)CollusionReal estateTragedy (event)PoliticsIncentivePopulationBusinessPublic administrationLawEconomicsPolitical scienceMarket economyFinanceSociologyIndustrial organization

Abstract

fetched live from OpenAlex

On 24 April 2013, Rana Plaza, a nine-storey building that housed five garment factories, a commercial bank and several retail shops, collapsed, killing more than 1,100 people. Had Bangladesh’s well-regarded building code been enforced, the tragedy would never have occurred. Through an exploration of the process by which real estate development projects are approved and building construction overseen, this article attempts to provide an explanation for why there is such a wide gap between formal policy and actual implementation. Following such tragic events, elected officials come under considerable pressure from civil society groups and citizens to pass stronger legislation, and Bangladesh’s political system, which concentrates power in the majority party and that party’s leadership, allows for the relatively easy passage of legislation. Nonetheless, dramatic population growth and limited availability of land create powerful incentives for developers to evade these regulations. Collusion between developers, the regulator and high-level government officials responsible for overseeing the regulator has ensured that both the laws and court orders are unenforced.

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.

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)0.002
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 score0.496
Threshold uncertainty score0.644

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.047
GPT teacher head0.290
Teacher spread0.243 · 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