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Record W4213111483 · doi:10.1017/s147959142100053x

From<i>The Good Earth</i>to<i>Mother India</i>: esthetic circulations of peasant womanhood between India and China

2022· article· en· W4213111483 on OpenAlexaff
Anup Grewal

Bibliographic record

VenueInternational Journal of Asian Studies · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicSouth Asian Cinema and Culture
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsPeasantChinaNexus (standard)NarrativeGender studiesPoliticsHistoryColonialismPolitical scienceGeographySociologyLiteratureArtLaw

Abstract

fetched live from OpenAlex

Abstract The mid-1920s to the 1950s witnessed the uneasy imbrication of the rural, the peasantry, and women as symbols and subjects of the nation in the era of anti colonial and socialist movements in both India and China. This essay examines this rural/peasant/woman nexus within conflicting representations of the peasant woman as embodiment of the nation's past, present and future, to map a range of connected global political-aesthetic imaginations of Indian and Chinese nationhood. A close analysis of the convergence of three texts – Pearl Buck's novel, The Good Earth (1931), Katherine Mayo's polemic, Mother India (1927), and Indian director Mehboob Khan's re-staging and transformation of both in his 1957 film, Mother India – opens up to a wider set of entangled Indian and Chinese co-texts within an expanded space of global aesthetic circulation. Together, these texts reveal a contested history of representations of the rural, the peasantry, and women in projections of Indian and Chinese national becoming that, in the end, cannot be easily recuperated or consolidated within singular nation-state narratives.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.614
Threshold uncertainty score0.566

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.263
Teacher spread0.241 · 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.

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

Citations0
Published2022
Admission routes1
Has abstractyes

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