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Record W4237582122 · doi:10.3138/utlj.60.2.349

IDEAS, INTERESTS, AND INSTITUTIONS: CONCEDING CITIZENSHIP IN BANGLADESH

2010· article· en· W4237582122 on OpenAlexvenueno aff
Ninette Kelley

Bibliographic record

VenueUniversity of Toronto Law Journal · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicBangladesh Politics, Society, and Development
Canadian institutionsnot available
Fundersnot available
KeywordsCitizenshipIndependence (probability theory)Human settlementGovernment (linguistics)State (computer science)Human rightsIdentity (music)Political scienceUrduWork (physics)SociologyPublic administrationLawEconomic growthGender studiesPolitical economyPoliticsGeographyEconomics

Abstract

fetched live from OpenAlex

For close to forty years, tens of thousands of Urdu speakers in Bangladesh did not exercise their rights as citizens, which they held in law but which were not recognized in practice. The roots of their marginalization were deep, stretching back to Indian independence and the creation of East and West Pakistan in 1947 and specifically to the divisions within Pakistan that existed at that time and were hardened during the Bangladesh struggle for independence in subsequent years. From the creation of the state of Bangladesh in 1971, this community lived in camps and settlements, without a legal identity and the associated rights to be educated, to work, and to participate in public life. The recognition by the government of Bangladesh in 2008 of their right to be registered as citizens was a significant human rights achievement. This essay tells the story behind this remarkable development and, using the framework for analysing the determinants of public choices advanced by Michael Trebilcock, examines the role that ideas, interests, and institutions played in this dramatic reversal of a long-standing public policy.

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)0.008
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0120.061
Scholarly communication0.0110.006
Open science0.0010.012
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0030.000

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 head0.030
GPT teacher head0.283
Teacher spread0.254 · 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 designNot applicable
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

Citations8
Published2010
Admission routes1
Has abstractyes

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Same venueUniversity of Toronto Law JournalSame topicBangladesh Politics, Society, and DevelopmentFrench-language works237,207