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Record W2810392754 · doi:10.1111/hic3.12461

Medieval English peasant women and their historians: A historiography with a future?

2018· article· en· W2810392754 on OpenAlexaff
Sharon Hubbs Wright

Bibliographic record

VenueHistory Compass · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical Gender and Feminism Studies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPeasantScholarshipAgency (philosophy)HistoriographySituatedGender studiesRemunerationSociologyMarxist philosophyRepresentation (politics)Social sciencePolitical sciencePoliticsLaw

Abstract

fetched live from OpenAlex

Abstract Scholarship concerning medieval peasant women grew out of economic, Marxist, legal, and social history and, since the late 1970s, has been taken up mainly by medieval scholars using feminist methodologies. This research has been conducted by a handful of scholars most actively working before 2000. A large portion of this research has been focused on recovering information about peasant women's daily lives, their occupations, and their remuneration for work. From this body of research, scholars have attempted to understand and demonstrate the social and cultural conditions which affected peasant women's status and their agency. While most agree that peasant women's lives were profoundly affected by gendered ideas, there has been debate about the degree to which patriarchal institutions and beliefs have limited women's lives. This article focuses on scholarship concerning peasant women situated in their own social milieu, rather than their representation in art and literature. It argues that there remain many opportunities for further research, especially in the form of team‐based research, which is becoming more common in digital humanities.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.999
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0070.010
Scholarly communication0.0050.004
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.019
GPT teacher head0.226
Teacher spread0.208 · 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.

Study designQualitative
DomainMethods
GenreReview

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

Citations2
Published2018
Admission routes1
Has abstractyes

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