The Major in Cultural Context: Choosing Liberal Arts in the Marshall Islands
Bibliographic record
Abstract
Choosing a major is part of liberal arts (LA) education in American-accredited colleges across the world. In global second-language (L2) contexts, the choice of major is shaped by local cultural factors. This study of 192 undergraduates at an English-medium-of-instruction (EMI) college in the Republic of the Marshall Islands (RMI) used a survey, content and Appraisal analyses to explore what the LA major means to RMI youth. Results showed they were positive about LA, but little engaged with it outside the classroom. This probably reflected the institution’s traditional concept of LA and outdated western teaching approaches, and a failure to incorporate elements of an authentic local culture of teaching and learning. Appraisal data indicated participants associated positive, congruent desire, interest and affection for the LA major, but also low utility and worth with LA class content, revealing a need to convey the utility of the LA skill set for employment. Finally, LA majors were intrinsically, whereas education, business and nursing majors were pragmatically motivated, reflecting the colonial heritage. Overall, results foreground the colonial character of current teaching practice, and the need to use authentic teaching and learning modalities, to support RMI students’ pragmatic needs, particularly given their emigration prospects.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".