Strengthening the Liberal Arts Along the Pacific Rim: The Pacific Alliance of Liberal Arts Colleges (PALAC)  
Bibliographic record
Abstract
While international alliances among research universities are relatively well established, the challenges for the small liberal arts college to execute a meaningful global collaboration can be much more difficult, due both to the much smaller size of the institution, its more limited resources, and its smaller and more intimate culture centered on undergraduate teaching and learning. A new alliance of liberal arts colleges known as the Pacific Alliance of Liberal Arts Colleges (PALAC) was established in 2021 with the purpose to better articulate the global components of liberal arts education, and to collaborate on key projects that will build collective capacity for student-centered liberal arts education that engages with the world’s most pressing problems. PALAC contains nine of the best liberal arts institutions from across the Pacific Region, including institutions in China, Hong Kong, Vietnam, Canada, and the United States. This essay describes the origins, motivations, and context of the creation of PALAC, its member institutions, and some of the initial projects planned by the new organization, and goals for global impact for PALAC.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.007 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".