The potential impact of the American liberal arts university model to post-conflict societies
Bibliographic record
Abstract
This study investigates the implications of importing an American liberal arts university model to post-conflict Iraq in order to anticipate its potential contribution to the ongoing processes of social cohesion and nation building. The study follows a qualitative research method using the American University of Iraq, Sulaimani (AUIS) in Kurdistan region as a case study. The study utilizes Holmes’ problem approach, which is based on a careful study of context to anticipate the implications of a borrowed model and what adjustments need to be made for a positive outcome. The initial findings show that the strong commitment to a liberal arts education is the cornerstone of AUIS. The not-for-profit private institution character is another important element of the university, yet it is confronted by the unstable economic and security realities of the country and the lack of understanding by some potential funders, which ultimately affects the provision of equal opportunities to students from different socio-economic status. It also affects campus diversity as a strategy to unite the country. International higher education practices became an attractive alternative to the failed status quo throughout Iraq’s territories. Not everyone, though, was assertive about the model’s applicability to other parts of Iraq.
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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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.020 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".