British Columbia in a Global Context
Bibliographic record
Abstract
Over the course of four days in June 2014, five Geography faculty members from across British Columbia, supported by a facilitator, librarian, researcher, illustrator, programmer and instructional designer, created this book.This involved drawing on our own research, teaching and experience and working with the team to put it all together into an online format, one that would be accessible to students and educators alike.Beyond the unique way in which this book was created through this Book Sprint process, there are other elements of this book that make it unique.First, it takes a holistic approach to first-year Geography, incorporating elements of physical, human and regional geography, as well as bringing in methods and perspectives from spatial information science.Pedagogically, this book is aimed at a a first-year or introductory Geography student, and would be suitable for a firstyear Geography course on BC.It incorporates elements of service learning and suggested service learning activities recognizing that the study of Geography is deeply connected to the communities we live in.Many of the suggestions for service learning are illustrated through the use of case studies from across BC.Finally, this book is openly
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.011 | 0.002 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.031 | 0.002 |
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".