A Letter to My Great-Great-Grandfather
Bibliographic record
Abstract
In a letter to her great-great-grandfather, Morgan Mannella presents the journey of her identity exploration alongside the Indigenous research that she discovered during her role as an assistant to the editors of the 3rd Edition of Racism, Colonialism, and Indigeneity in Canada. The letter includes discussions with Morgan’s mentor, Dr. Lina Sunseri, one of the editors of the textbook. Morgan offers her personal story to express her position as an emerging Indigenous scholar. As a woman of both Indigenous and white settler heritage, Morgan demonstrates anxiety and disorientation early in her identity and project journey but displays optimism that assisting with the textbook will ease her head and heart. In four sections, Morgan describes several Indigenous topics including criminality and criminalization, environmental racism, poverty and development, and resistance. The four topics exemplify settler colonial racism against Indigenous peoples and present ways of how Indigenous peoples can combat the various forms of non-Indigenous oppression. At times, Morgan offers her personal thoughts and feelings regarding the knowledge that she has learned as she allows herself to decolonize her Eurocentric knowledge biases and listen to several Indigenous voices. The topics, alongside the accumulation of water droplets that have been drawn on the pages of the letter, represent Morgan’s growth in knowledge and understanding as she discovers more information and findings during her reading. The conclusion of the letter reveals a reconciliation of Morgan’s dual identity and a commitment to using the knowledge that she has learned to continue to decolonize and indigenize her life in honour of her ancestors who had long been unknown to her.
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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.033 | 0.011 |
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".