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A Kaddish for the Father: Régine Robin and the “impossible work of mourning”

2016· article· en· W2509266185 on OpenAlexaffabout
Kathleen Kellett

Bibliographic record

VenueStudies in American Jewish Literature (1981-) · 2016
Typearticle
Languageen
FieldPsychology
TopicPsychoanalysis and Psychopathology Research
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsDaughterVenerationThe HolocaustNazismDeportationHistoryCommunismWhite (mutation)GenealogyArt historySociologyArtPoliticsLawAncient historyImmigrationArchaeologyPolitical science

Abstract

fetched live from OpenAlex

ABSTRACT This essay examines the father-daughter relationship and the dynamics of mourning in the biofiction of Quebec author Régine Robin, born Rivka Ajzersztejn in 1939 in Paris. Focusing on her first work of biofiction, Le Cheval blanc de Lénine (1979), as well as the short text “Manhattan Bistro” (1992), I argue that Robin presents the daughter’s tale as both an act of defiance against paternal authority and her Communist father’s veneration of the great men of history—incarnate in the vision of Vladimir Lenin on a white horse—and homage to her father’s role as inventive and passionate chronicler of family history. The daughter recounts her father’s struggle with the refusal to say the Kaddish for his own father, an impossible act of mourning mirrored by the Kaddish that could not be recited for the fifty-one members of her family lost in the Holocaust. Robin’s biofiction is an unceasing iteration of the grieving process, an examination of the vagaries of memory and history, and the arbitrary accidents in time that led to deportation to the Nazi death camps for some and survival and a future life in North America and elsewhere for others.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.598
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.032
GPT teacher head0.378
Teacher spread0.347 · 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.

Study designNot applicable
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
Published2016
Admission routes2
Has abstractyes

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