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Record W2805392171 · doi:10.7202/1058071ar

“Memories Seeded in Longings”: An Interview with Bernice Eisenstein

2019· article· en· W2805392171 on OpenAlexvenueno aff
Ruth Panofsky

Bibliographic record

VenueStudies in Canadian Literature · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicRace, History, and American Society
Canadian institutionsnot available
Fundersnot available
KeywordsSeedingArtPsychologyBiologyAgronomy

Abstract

fetched live from OpenAlex

rtist and writer Bernice Eisenstein (1949-) was born in Toronto to Polish Holocaust survivors.Her father, Barek (Beryl or Ben) Eisenstein, was from Miechow and her mother, Regina Oksenhendler, was from Bedzin; both survived Auschwitz.They immigrated to Canada in 1948

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)0.007
metaresearch head score (Gemma)0.019
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: none
Teacher disagreement score0.580
Threshold uncertainty score0.835

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0300.022
Scholarly communication0.0060.007
Open science0.0020.003
Research integrity0.0060.011
Insufficient payload (model declined to judge)0.0020.000

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 head0.317
Teacher spread0.297 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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