Re-Writing/Righting History Through Storytelling: Memory, Identity, and Trauma of Forced Child Removal in Contemporary Indigenous Fiction
Bibliographic record
Abstract
The history of American Indian boarding schools had been mostly unknown until a few decades ago. A recent upsurge of writings on this topic across the United States of America and Canada has brought to light the inside perspective, making the damaging effects of the cultural reprogramming through education that affected thousands of Indigenous children for over a century visible and clear. This thesis explores the issues of alienation, trauma, memory, and identity crisis resulting from the forced removal of Indigenous children and their exposure to mainstream education in off-reservation boarding schools during their formative years. It analyses Debby Dahl Edwardson’s novel My Name is Not Easy (2011) and three nonfictional texts – K. Tsianina Lomawaima’s They Called It Prairie Light (1994), Christy Jordan-Fenton and Margaret Pokiak-Fenton’s memoir Fatty Legs (2010), and Laura Tohe’s No Parole Today (1999). All of these texts re-write/right the history of the boarding-school era by emphasizing the assimilation policy as the central component of Indian residential schools’ programme. They reveal not only the negative but also the positive side of the students’ experience as well as the fact that these schools frequently became sites of resistance and resilience in which the disciplinarians’ rules were subverted and Native identity maintained through students’ mutual support, friendship, and solidarity. Although the students sometimes managed to claim the power of the boarding schools for themselves and even though, despite the government’s efforts to destroy their connections to the tribal communities, many of them returned from school even stronger and with the knowledge of many new skills, effects of the boardingschool trauma and discrimination are felt even today as the lingering issues of depression, suicide, and substance abuse continue to plague Native communities. The final part of this paper looks into those issues and explores the possibility to alleviate them by incorporating cross-cultural knowledge and Indigenous teaching methods in contemporary mainstream school curricula.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.035 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".