Is the Achievement of Moral Character the Ultimate Goal of Higher Education?
Bibliographic record
Abstract
This article is to explore whether the achievement of moral character is the ultimate goal of higher education from a cross cultural approach. To discuss this study logically, three major research questions are addressed. First, what are the concepts of moral, ethics, and character? Second, what is the achievement of moral character from the Eastern and the Western perspectives? Third, what is the role of higher education for the achievement of moral character? To defend these research questions, the author uses a descriptive content analysis method, with a cross cultural approach. In order to explore the questions, the researcher in this study sets several limitations. Moral character is generally limited to the ancient Greek philosophy and Judeo-Christianity as well as to the classical Chinese thought and religion. Specifically, the study is mainly focused on not only Plato's "Republic" and Aristotle's "Nicomachean Ethics," but Confucius' "Analects" and Mencius' "Scripture (The Works of Mengzi)." Additionally, this paper also adjusts the lenses on moral theories, especially moral character, cardinal virtues, social harmony, and the common good. Lastly, higher education is focused on the lenses of Canada and South Korea. The significance of this study is to provide basic theories and valuable resources about moral and character education for educational theorists and practitioners, finding the theories of moral and ethics in the Eastern and the Western thoughts and religions.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".