Analysis of Factors Affecting Digital Textbook Pricing in Korea
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The use of paper books for teaching and learning has many limitations in terms of cost and efficiency. The advantages of digital textbooks are emphasized in many studies. Researchers say that the use of digital textbooks as mediators of the 21st century provides the ability to solve a variety of educational and learning problems for the future. However, many stakeholders in education, such as teachers, students, parents, publishers and educators, are not prepared to accept it and infrastructure is incomplete. In Korea, digital textbooks are used in classrooms in 2018. Publishers are creating new digital textbooks containing sophisticated digital content in accordance with government guidelines, teachers want to create customized lessons for each student level, and profitability and market expectations are changing the importance of digital asset pricing in the textbook market. In this paper, we explore factors that affect digital textbook pricing, to help publishers maximize revenue over their product lifecycle.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 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 it