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Record W7111897354

“Five Little Indians: A Narration of Trauma and Witnessing”

2025· book-chapter· en· W7111897354 on OpenAlexaboutno aff

Bibliographic record

VenueIRIS Research product catalog (Sapienza University of Rome) · 2025
Typebook-chapter
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsWitnessIndigenousNarrativeSexual abuseCharacter (mathematics)Work (physics)
DOInot available

Abstract

fetched live from OpenAlex

Residential schools operated in Canada from 1876 to 1996 on the intention to assimilate Indigenous children to Euro-Canadian culture. Under the authority of the Indian Act (1876), Indigenous children were taken away from their parents and sent to these schools. The trauma that these children experienced as a result of physical, mental, and sexual abuse at these residential schools is reflected in Michelle Good’s novel Five Little Indians (2020). This novel is based on Judith Herman’s conception of trauma and Shoshana Felman and Dori Laub’s notions of witnessing and testimony, which support the idea a literary work can bear witness to historical incidents that occurred at residential schools in Canada. The various characters in Good’s novel describe their experiences of these schools and follows their lives after escaping or completing their schooling. Each character narrates their stories and describes their plight during and after their time at a residential school. As such, the chapter will further discuss how the novel’s characters exhibit traumatic symptoms as a result of the hardships they experienced.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.712
Threshold uncertainty score0.580

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0430.020
Scholarly communication0.0060.003
Open science0.0030.005
Research integrity0.0040.009
Insufficient payload (model declined to judge)0.0040.001

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 head0.040
GPT teacher head0.325
Teacher spread0.285 · 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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueIRIS Research product catalog (Sapienza University of Rome)Same topicIndigenous Health, Education, and RightsFrench-language works237,207