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Record W2922862100

‘Can I speak? If I can, I speak what you want me to speak’: Negligence to the Adivasi Language in the Bangladeshi Education System

2018· article· en· W2922862100 on OpenAlexaff
Tanzina Tahereen

Bibliographic record

Venue2019 Conference of the Canadian Society for the Study of Education · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSouth Asian Studies and Conflicts
Canadian institutionsQueen's University
Fundersnot available
KeywordsColonialismSociologyOppressionGender studiesIndigenousIdentity (music)PoliticsPolitical scienceLawAesthetics
DOInot available

Abstract

fetched live from OpenAlex

This paper presents a frame analysis of the state and education policy and Bangladeshi practices regarding its negligence towards the Adivasi (indigenous) languages in the education system for the Adivasi students through the lens of Linguicism and Critical Race Theory (CRT). This analysis argues that the policy of equal and same education for everybody titled ‘education for all in Bangla’ promotes the overarching sentiment of Bangali nationalism rooted in Bangla language, and endorses inequitable though racist practices for the Adivasi people in Bangladesh. Also, I demonstrate that the attitude of ‘disavowal’ for the Adivasi languages as well as knowledge feeds on existing identity politics regarding ‘indigeneity’ and the assimilation process. Finally, while portraying the dominant attitude of the power structure (political/social Elite) of misrecognition and disregard for the existence of these Adivasi people as well as their languages within the education system, this analysis shows how education, a colonial legacy has been used as a technology of power to propagate ongoing colonialism, oppression and discrimination in Bangladesh. Therefore, this article attempts to delineate how such discriminatory educational policies and practices towards the Adivasi reflect the underlying ideologies of centralization, homogenization, standardization, hierarchization and colonization.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.337
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.030
GPT teacher head0.306
Teacher spread0.276 · 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.

Study designQualitative
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

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venue2019 Conference of the Canadian Society for the Study of EducationSame topicSouth Asian Studies and ConflictsFrench-language works237,207