A Cop, a Thief, and a Priest ...and some bad grammar: An Unruly Un-Love Story and the First Nations Fiction Diction Essay That Goes With It
Bibliographic record
Abstract
This dissertation is comprised of two distinct but related components. The larger component is a short novel, titled A Cop, a Thief and a Priest. This is the story of three very different men, the woman they all want, her daughter who gets in the way, the secrets they all try to hide, and a few bedtime stories. Plus a Canadian Native or two. And maybe a bomb, as well. This work of fiction is written with a shifting perspective and varying degrees of adherence to the rules of grammar, depending on the narrator and characters in the scene. The story focuses on seriously flawed people in potentially harmful, though ceaselessly humorous, relationships and how they try to choose the best out of the poor options in front of them. In the course of the novel several Native Canadian/First Nations characters appear. Some are characters within the story, and others are cast members of several bedtime stories told by the three primary male characters. As I am not Canadian First Nations, I had concerns over writing dialogue and characterization of Canadian Native characters. In response to these misgivings, the accompanying critical essay component of this dissertation deals with the issue of a non-Native author writing Native characters. The thesis essay explores this question in the fiction of three Canadian authors who are not Canadian First Nations. I examine specifically their use of grammatical errors in the dialogue of their Native characters as a device to present diction as an element of the character’s status, education, gender, age, race or culture. The three authors chosen are W.P Kinsella, Anne Cameron, and Thomas King. These writers use diction variously, and each is scrutinized according to guidelines drawn from writing theory texts, commercial writing guides, and writing practice prescriptions from successful authors. The conclusions are considered in the crafting of my own First Nations characters.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.024 | 0.015 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".