MétaCan
Menu
← Back to cohort
Record W4399608742 · doi:10.58532/v3bblt2p2ch10

THE QUEBEC NOVEL IN MULTI PERSPECTIVES

2024· book-chapter· en· W4399608742 on OpenAlexaboutno aff
Ms. Banu Priya A, K. Thiyagarajan

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsIdeologyNationalismPoliticsIdentity (music)SociologyHistoryAestheticsMedia studiesGender studiesHumanitiesArtPolitical scienceLaw

Abstract

fetched live from OpenAlex

THE QUEBEC NOVEL of the last decade in many ways radically different from those of present -classic texts of the 1960s that first attracted the attention of American critics. Those novels seemed borne on the wave of a new sense of national identity associated with Quebec’s Quiet Revolution. A bursting of the forth creative activity made names like Marie-Claire Blais, Hu-bert Aquin, Michel Tremblay, Jacques Godbout, Anne Hébert, and Réjean Ducharme familiar even to an American public. Together, these writers produced a sense of a lively new Quebec, satirizing the complacent of old ways and looking toward new, even revolutionary forms of political and artistic expression. Following closely on their heels, a generation of feminists translated this sense of newly-emerging identity from nationalism to gender, and writers like Nicole Brossard, France Theoret, Madeleine Gag- non, and Louky Bersianik became the spokespersons for an active feminist movement that broke with traditional generic models and experimented with language as a means of representing difference. Emerging from a remarkably close-knit intellectual community located primarily in Montreal, the major Quebec novelists of the 1960s and 1970s seemed to share similar concerns, often ideological as well as artistic, and to participate in a homogeneous society, whereas one undergoing rapid change.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.102
Threshold uncertainty score0.740

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0250.011
Scholarly communication0.0110.003
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0220.001

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 head0.028
GPT teacher head0.261
Teacher spread0.233 · 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

Explore more

Same topicCanadian Identity and History→French-language works237,207→