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Record W3138256945 · doi:10.21810/strm.v12i1.279

Re-writing history

2020· article· en· W3138256945 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueStream Interdisciplinary Journal of Communication · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicOral History, Memory, Narrative Analysis
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsOral historyNarrativeScholarshipGender studiesSection (typography)Women's historySociologyHistoryWorld historyLiteratureAnthropologyPolitical scienceArtLaw

Abstract

fetched live from OpenAlex

Feminist historians (Kelly, 1984; Scott, 1998) have argued that documented History is inherently ‘masculine’ and marginalizes women’s life experiences. In order to bridge this gap in History, feminist oral historians in the 1970s began collecting women’s oral testimonies to highlight their subjective experiences (Patai and Gluck, 1990). Building on existing scholarship, this paper argues that oral history as a methodology is indispensable in a feminist re-writing of history. It analyzes oral histories conducted by Indian feminist historians with women survivors of India’s Partition. The first section uses a gendered historical lens to argue that feminist oral history is crucial to writing a women’s history. The second section outlines what constitutes as a feminist methodology to envision what women’s history should look like. The final section examines the difficulties of working with oral testimonies. The objective of this study is two-fold: examining non-hierarchical ways of researching through feminist oral history and drawing attention to oral narratives in the global south.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.764
Threshold uncertainty score0.998

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.067
GPT teacher head0.292
Teacher spread0.224 · 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