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
Adoption of ePortfolio tools in higher education has been implemented in individual courses, departments, schools, and across institutions to demonstrate evidence of more authentic student work, show student progress over time, and represent collections of best work. New technologies have enhanced the learning affordances of ePortfolios to include its usefulness as a tool to support integration, synthesis, and re-use of formal and informal learning experiences. The challenge for educators is to develop new pedagogical approaches to encourage students to recognize and extend the value of ePortfolio software beyond simple course applications and outside the context of their undergraduate education. This chapter describes the learning landscape model, a conceptual framework which promotes a view of “learning” that supersedes the rigid structure of degree outlines and requirements by taking advantage of a variety of technologies to incorporate overlapping experiences through social networking among faculty, mentors, peers, and employers and resources.
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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it