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Record W7070734840

Reclaiming the Personal: Oral History in Post-Socialist Europe. Ed. Natalia Khanenko-Friesen and Gelinada Grinchenko. Toronto: University of Toronto Press, 2015. 328 pages.

2020· article· en· W7070734840 on OpenAlexaffabout

Bibliographic record

VenueIndiana Magazine of History (Indiana University) · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicOral History, Memory, Narrative Analysis
Canadian institutionsECW Press (Canada)
Fundersnot available
KeywordsOral historyInterviewValue (mathematics)EthnographyPoliticsHistory of anthropologyCultural historyCultural anthropology
DOInot available

Abstract

fetched live from OpenAlex

The last few decades in humanities and social sciences revealed that scholars tend to work interdisciplinarily, emphasizing on the value of holistic approaches while researching societies and human interactions.This volume is framed as interdisciplinary research, gathering writings of oral historians, cultural anthropologists and sociologists.Therefore, it will be of interest to a wide scholarly audience.Cultural anthropology and oral history share two important features.Theoretically each discipline aims to make voicelessness vocal, in other words, to give voices to those who are absent from history textbooks and whose lives don't fit in current national projects and political ideologies.Neither oral historians nor cultural anthropologists are interested in revealing the "true" or "objective" past.Instead they deal with people's personal interpretations of the past.Methodologically both disciplines use the method of interviewing to record a person's narration, documenting people's life

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.018
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0030.008
Scholarly communication0.0080.007
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.002

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 head0.034
GPT teacher head0.193
Teacher spread0.160 · 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 designNot applicable
Domainnot available
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

Citations0
Published2020
Admission routes2
Has abstractyes

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