Bibliographic record
Abstract
The University of British Columbia Press (UBC Press), like many other university presses (UPs), has been outsourcing ebook production since it first started publishing its titles in digital form in the late 1990s. For over a decade, these files have been created by foreign companies hired through third parties—initially, through content aggregators, and more recently, through the Association of Canadian Publishers. At first, outsourcing seemed a sensible way for UBC Press to enter into e-publishing: the practice was not only convenient and cost effective, but it also fit with the Press’s own freelance-based business model. However, by 2011, it had become evident that outsourcing to large conversion houses had a number of drawbacks. In its most recent outsourcing experience, UBC Press had to deal with poorly formatted files, protracted production timelines, and delayed distribution, which has in turn threatened the reputation of the press and the profitability of its ebooks. Added to these problems are greater, industry-wide disadvantages that may result from outsourcing en masse, such as a dependence on cheap overseas labor and missed opportunities for professionalization and skill development among Canada’s domestic workforce. In the face of these problems, individual publishers like UBC Press must put various short-term solutions in place and consider making changes to their own production workflows if they are to achieve greater quality assurance and control over their own epublishing programs.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".