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Record W2970797082 · doi:10.5539/ijel.v9n5p249

A Feminist Critical Discourse Analysis of Qaisra Shahraz’s The Holy Woman in the Backdrop of Subalternity

2019· article· en· W2970797082 on OpenAlexvenueno aff
Hadia Khan

Bibliographic record

VenueInternational Journal of English Linguistics · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicPolitics and Conflicts in Afghanistan, Pakistan, and Middle East
Canadian institutionsnot available
Fundersnot available
KeywordsSubalternObjectificationGender studiesSociologySubject (documents)Power (physics)Critical discourse analysisDiscourse analysisPremiseIdentity (music)PoliticsEpistemologyAestheticsIdeologyPolitical scienceArtPhilosophyLawLinguistics

Abstract

fetched live from OpenAlex

This paper analyzes the objectification of the South Asian female subject as subaltern by the patriarchal power structure, and disrupts the relevant discourse practices. It investigates this notion in Qaisra Shahraz’s novel The Holy Woman. Methodologically, it applies Gayatri Spivak’s perspective of the subaltern to establish its ontological premise. Additionally, it uses Lazar’s concept of Feminist Critical Discourse Analysis to deconstruct the power discourse behind the objectification of the female identity as reflected in the selected text. The analysis of the selected text reflects as the South Asian patriarchal society ‘legitimizes’ the ‘othering’ of its female subject for the fulfilment of its power agenda that involve political and economic interests. The analysis also reveals as dominant discourse interprets religion the way it suits the power structure. It also shows how the female subject realizes its manipulation by acquiring the knowledge which she earlier lacked and on the acquired awareness, resists the power structure. Through its methodological approach, the paper incites further research into the reorientation of subalternity in the South Asian context.

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)0.003
metaresearch head score (Gemma)0.003
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: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.013
Scholarly communication0.0050.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.025
GPT teacher head0.372
Teacher spread0.348 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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