Book Review: Nii Ndahlohke: Boys’ and Girls’ Work at Mount Elgin Industrial School, 1890-1915
Bibliographic record
Abstract
Nii Ndahlohke is a Lunaape word that translates as "I work" in English.It is an appropriate title for this short but informative book about student life and child exploitation at the Mount Elgin Industrial School.Residential School histories are being written with increasing and welcomed frequency.Works like Nii Ndahlohke help elucidate this national history by showing how schools operated and impacted Indigenous people in specific areas.Focusing on how children at Mount Elgin were forced to provide free labour to maintain the school, McCallum illustrates how this school not only failed to provide Indigenous children with a useful education but also exploited those children to support the same school that was, in turn, harming them.The history McCallum recounts is made more poignant when she relates that it was First Nations living at what is today the Chippewa of the Thames First Nation who wanted the school built.As was the case with other Indigenous requests for European schooling, the parents' original intent to help their children was quickly perverted by missionary groups and government officials.Children became the victims of underfunded, poorly run, badly supervised, utterly inadequate schools that provided inadequate education to the students even by late nineteenth and early twentieth century standards.Mount Elgin was classified as an "industrial school" with local students attending as day students and other students from as far north as Wausauksing First Nation (near Parry Sound), as far east as Curve Lake First Nation, and as far west as Walpole Island
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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 | 0.001 | 0.003 |
| 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 | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.042 | 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".