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Record W2612689061 · doi:10.1080/1369801x.2017.1320226

Education Intercepting The Dalit Way of Being

2017· article· en· W2612689061 on OpenAlexaff
Sarbani Banerjee

Bibliographic record

VenueInterventions · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicSouth Asian Studies and Diaspora
Canadian institutionsWestern University
Fundersnot available
KeywordsSociologyComputer science

Abstract

fetched live from OpenAlex

Through readings of Adhir Biswas’ memoirs – Deshbhager Smriti [2010 Biswas, Adhir. 2010. Deshbhager Smriti. 4 vols. Kolkata: Gangchil. [Google Scholar]. 4 vols. Kolkata: Gangchil] and Allar jomite paa [2012. Kolkata: Gangchil] – as well as Manoranjan Byapari’s autobiographical work Itibritte Chandal Jibon (2012), I study the importance of education in the lives of first-generation literate Bengali Dalit immigrants. I evaluate the journey of Biswas and Byapari from being labelled as “chhotolok”, towards becoming a part of the bhadralok social group, redefining what it means to belong to either group. I observe how education enables incorporation of these writers into the mainstream elite lifestyle and why this process of assimilation is riddled with difficulties from both ends. By briefly referring to the antagonistic relationship between the subalterns and the landlords in the Indian scenario, I note how traditional social markers of the colonial bhadralok are increasingly challenged in the postcolonial period by the non-bhadralok masses through unconventional counter-narratives. Furthermore, I discuss the role that education plays in legitimizing the position of marginalized people, such as refugees, in post-partition India. How does literacy change the perspectives of Dalit refugees towards their surroundings, and what significance does the act of writing hold for them?

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.027
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.031
Scholarly communication0.0100.005
Open science0.0010.008
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0080.001

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 head0.098
GPT teacher head0.343
Teacher spread0.245 · 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 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

Citations1
Published2017
Admission routes1
Has abstractyes

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