Leaving the Reservation: Reconstructing Identity in Sherman Alexie’s The Absolutely True Diary of a Part-Time Indian
Bibliographic record
Abstract
Sherman Alexie is an acclaimed Native American author who writes about growing up on the Spokane Indianreservation and the harsh realities of widespread poverty and alcoholism. This paper aims to examine hisreconstruction of Native American identity in his young adult novel, The Absolutely True Diary of a Part-TimeIndian. This book presents a Native American’s education, culture, and wounds through the eyes of a teenage boynamed Arnold. The phrase “absolutely true diary” hints at the semi-autobiographical nature of Alexie’s novel; likeArnold, Alexie grew up on the Spokane Indian Reservation and transferred to the all-white high school in Reardon toescape the hopelessness of the rez. The words “part-time” signify Arnold’s struggle to reconcile his disparateexperiences in the white world and the Indian world. Caught between the two, he must reconstruct his NativeAmerican identity to find his own place in the world.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.018 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".