Review of <i>With Good Intentions: Euro-Canadian andAboriginal Relations in Colonial Canada</i> Editedby Celia Haig-Brown and David A. Nock
Bibliographic record
Abstract
This collection of essays focuses on a specific group of Euro-Canadians: those who "recognized injustices" and "allied themselves with Aboriginal people who also saw the injustices and were actively resisting them, and worked in a variety of ways to address them." Yet the authors approach their subjects with a critical eye, realizing many of these efforts were concentrated on aboriginal peoples who missionaries thought adopted "appropriate and/or useful aspects of Christianity, European dress, and settlement into farming villages or business ventures." Additionally, the authors realize some of the actors in the book "struggle[d] to reconcile their Christian morality with their own desires to get ahead." Under this rubric of analysis, the chapters analyze such varied people as anthropologist Horatio Hale, aboriginal activist Nahnebahwequa, and the missionaries E. F. Wilson and Emma Crosby. Each chapter provides in-depth background to its specific subject, and most chapters locate the transformation of their subjects within the debates of the time period. The volume thus provides excellent background for anyone seeking to use missionary documents for ethnographic, geographic, or other analysis by helping to decode the biases and inherent holes. the book's only weakness lies in its editors' reticence about the importance of their work. While claiming that they hope these essays encourage others to look at missionaries as important sources, the introduction wastes time treading familiar and not very fertile ground about the history of colonialism and racism. If their audience is truly those who have dismissed missionaries, then they needed to sing the praises of their own essays instead of apologizing for doing "white studies rather than Native studies." The volume's strength is twofold. First, it uncovers those rare missionaries who bucked the system and fought colonial injustice, even if in limited and biased ways. These exceptions help us understand mainstream actors and their fears and motivations. Second, and perhaps most important, it helps demystify missionaries and the resources they left behind. They are no more and no less biased than other sources, yet social scientists have shied away from them. With Good Intentions provides the means to approach missionaries in a critical and balanced manner, and that is its greatest contribution to the field.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.009 | 0.028 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".