EBOOKS AS A MANDATORY TEXT IN LARGE FIRST YEAR GENERAL EDUCATION GEOSCIENCE COURSE
Bibliographic record
Abstract
Ebook study -Why? In science the cost of textbooks is prohibitive.Ebooks are often as much as 50% cheaper Many textbooks companies are moving to more online resources, particularly for large introductory level courses For the course in this study, no single hardcopy or even custom text was suitable to the material, W.W. Norton & Company Inc. agreed to provide a package which accessed two texts for the course as an ebook. Ebook Study -Why? On review of the literature, little or nothing was present on the required text in a course being in electronic form only most studies address this with the ebook as an option This course was offered in both in class lecture and fully online and has a diverse student population from many programs and from all 4 years of study As such, it was felt this was a unique opportunity to gauge student reaction and experience in using the ebook format, and to address such issues as might arise.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.197 | 0.058 |
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".