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Record W4405798320 · doi:10.46793/lld24.226m

ITALY REVISITED. CONVERSATIONS WITH MY MOTHER BY MARY MELFI, A DIALOGUE BETWEEN A MOTHER AND A DAUGHTER

2024· article· en· W4405798320 on OpenAlexaboutno aff
Rosina Martucci

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicItalian Fascism and Post-war Society
Canadian institutionsnot available
Fundersnot available
KeywordsDaughterPsychologyComputer scienceSociologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

The Italian-Canadian writer Mary Melfi is the author of a memoir entitled “Italy Revisited. Conversations with my Mother”, published in Canada by Guernica Editions in 2009. This work represents an anthropological fresco of unexpected depth and richness. The memoir presents conversations between a mother and a daughter who wants to know her origins and the story of life in a village of Southern Italy. Both protagonists are women of Italian origin who have emigrated to Canada, but they demonstrate polarized forms of self-representation and compensation for their displaced circumstances. The protagonist/narrator directly articulates the oppressive stigma of her tattered identity because she is the everyone and no-one in the immigrant experience; she has a past and varied history that she will ultimately exchange for a new identity. The irony in Melfi’s narrative may be understood as a device to redeem the meaning of selfhood against value-assigning roles in society. Conversations and writing become a liberating medium that reconciles the protagonists and the same author to their past and identity. However, the memoir can be considered a reconciliatory text hinging on the figures of the mother and daughter, who finally reconstruct a past – their suffered and never forgotten family past.

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)0.003
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.433
Threshold uncertainty score0.861

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0210.010
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0020.001

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 head0.011
GPT teacher head0.257
Teacher spread0.246 · 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
GenreOther

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
Published2024
Admission routes1
Has abstractyes

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