Eight Patterns of Open Textbook Adoption in British Columbia
Bibliographic record
Abstract
Since the launch of the BC Open Textbook Project in 2012, the adoption of open textbooks has steadily grown within public post-secondary institutions in British Columbia, Canada. An analysis of adoption records over a five-year period reveals that open textbooks have been adopted across all types of institutions, including research universities, teaching universities, colleges, and institutes, and across a diverse set of disciplines, with the largest numbers in the sciences and social sciences. In this report we identify, describe, and illustrate eight distinct patterns of open textbook adoption. These are: stealth adoption, adoption by infection, committee adoption, sanctioned exceptional adoption, course developer adoption, infection by inter-institutional carrier, creation and adoption, and lone adoption. While these patterns are not intended to be exhaustive, we hope that identifying these patterns provides a useful framework for campus leaders to (a) understand how adoptions occur in their own contexts, (b) identify ways to support further adoptions, (c) recognize that there are multiple ways, and no single path, to supporting the adoption of educational innovations at their institutions, and (d) foster the embrace of wider open educational practices.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.021 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".