Book Review of Robertson, David A. (2020). Black Water: Family, Legacy and Blood Memory. Toronto: HarperCollins Publishers.
Bibliographic record
Abstract
David Alexander Robertson's memoir, "Black Water: Family, Legacy, and Blood Memory," examines the complexity of Indigenous identity, generational trauma, and the lasting effects of the Canadian residential school system.Through visual art and narrative, Robertson provides an in-depth exploration of Indigenous issues, creating a narrative that captivates readers and conveys his voice in a way that resonates with Indigenous readers."Black Water" begins with Robertson sitting in a café with his father, Don, one of many locations Robertson speaks about in this memoir.Don wishes to return to his trapline one last time, where he has not been for almost seven decades (Prologue).Don, born in 1935, lacked official Indigenous status despite his heritage.For nine months each year, he and his family resided in a camp on their trapline in Canada.However, their way of life transformed with the enactment of the Family Allowances Act in 1945.This legislation offered financial assistance to children with a fixed residence, forcing Don's family to relinquish their trapline, except for short seasonal visits in the spring (Chapter 6).Robertson accepts his father's request, beginning the documentation of Robertson's journey to a more profound knowledge of family and identity, a quest for self-discovery and mending between father and son.Within "Black Water," Robertson skillfully interconnects three themes: Family, Legacy, and Blood Memory.As Robertson recalls stories from his youth and his efforts
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.032 | 0.015 |
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".