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Record W1972015922 · doi:10.1080/03050718.2012.694998

International practice of Public Legal Education: a missing element in the justice system of Bangladesh

2012· article· en· W1972015922 on OpenAlexaboutno aff
Taslima Yasmin

Bibliographic record

VenueCommonwealth Law Bulletin · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Education and Practice Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsVariety (cybernetics)EmpowermentTransformative learningRelevance (law)Economic JusticeElement (criminal law)Public relationsSubject (documents)Political scienceProcess (computing)Order (exchange)SociologyPublic administrationEngineering ethicsLawBusinessEngineeringComputer sciencePedagogy

Abstract

fetched live from OpenAlex

Public Legal Education (PLE) is a recently developed international practice which aims at providing nationwide legal education and information services to the public by way of a variety of innovative methods. Compared to its presence in a number of developed countries, the practice of PLE is not very common in least developed and developing countries such as Bangladesh. However, its impact on the process of legal empowerment could be transformative. This article thus attempts to assess the necessity and the prospect of introducing PLE in Bangladesh. In doing so, the concept of PLE will be analysed first, focusing on the various methods that are applied for its delivery. Considering the presence of comprehensive PLE practices, the PLE framework in two other jurisdictions – Canada and Australia – will then be examined in order to achieve a comparative view on the subject. Upon analysing the relevance of PLE, the article will finally propose a number of key recommendations to introduce a PLE framework into Bangladesh.

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)0.005
metaresearch head score (Gemma)0.009
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 score0.019
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0070.014
Scholarly communication0.0080.004
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.064
GPT teacher head0.405
Teacher spread0.341 · 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

Citations1
Published2012
Admission routes1
Has abstractyes

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