TOWARD A DESIGN FRAMEWORK FOR INTERNATIONAL PEER DISCUSSIONS: TAKING ADVANTAGE OF DISPARATE PERSPECTIVES ON SOCIO-SCIENTIFIC ISSUES
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
This paper describes how we have adapted the WISE technology and curriculum for use in an international setting. We also report on a cross-cultural collaboration between the two authors, representing the WISE project in the U.S. and its counterpart, called Viten (see http://viten.no) in Norway. After introducing the WISE platform and describing our collaboration, we present a brief comparison of the Norwegian and U.S. educational systems. We then describe “Viten.no,” the national level program that has grown around this effort. Next, we present our designs for a collaborative activity where students from our two countries first perform a WISE (or Viten, respectively) inquiry project concerning wolf populations and biodiversity, followed by a sequence of online discussions designed to capitalize on cultural and geographic differences for purposes of conceptual learning. Finally, we describe the outcomes of our classroom trials of this international curriculum, which are limited in scale but sufficient to allow the framing of some design principles. We close with a discussion of the implications of such curriculum, and our own current efforts to continue this line of research.
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 | 0.015 | 0.152 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.005 |
| 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