The Black-Sheep of the Canadian Book Trade: An Exploration of the Current State of Self-Publishing in Canada
Bibliographic record
Abstract
The following thesis explores the exclusion of the self-publisher from the publishing sector in Canada. Even though the self-publisher has been a part of the Canadian publishing sector since the 1960s, this type of business model is not acknowledged as a legitimate form of book production. The thesis utilizes mixed methods to create a metanarrative of how the self-publisher is viewed in the publishing industry. The quantitative portion of the thesis employs descriptive statistics in order to summarise the data of how the Canada Book Fund was distributed over a three-year period from 2016-2018. The qualitative portion utilizes a narrative policy analysis of various government documents including the Canada Book Fund guidelines, Creative Canada policy framework, and the guidelines of the different provincial art councils. Through this analysis the study highlights the discourse around self-publishing and how the self-publisher is excluded from the funding models. Furthermore, the reports of the key players of the industry similarly do not acknowledge the self-publisher as a legitimate member of the book trade. The last section investigates what concepts/themes/ideas self-publishers emphasise about the self-publishing industry themselves, which are agency and legitimacy. Through recognizing the discourse linked to the self-publishing infrastructure, the thesis concludes with some suggestion on how to alter this infrastructure in order for the self-publisher to become a legitimate member of the Canadian publishing industry.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.014 |
| Science and technology studies | 0.045 | 0.027 |
| Scholarly communication | 0.018 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".