Path of Khruba: Leadership for Empowering Good Citizenship
Bibliographic record
Abstract
“Path of Khruba” is a discourse created in the context of Lanna society, to reflect the practice and attributes of monks in beautiful Buddhism, to be good and practice, as well as to be firm in dharma discipline, as well as to be highly respected of the people’s faith and to contribute significantly to the development of people and society. According to the study of Khruba practice in Lanna society, the “Path of Khruba” is the most popular. There are five key points of good citizenship: (1) Sujarittham, who focuses on non-corruption, public property of the community or the society in which they live (2) Karawatham, focus on citizens to respect the law, the rules and laws that the community or society have together designed and accepted are common practices (3) Sangkhahatham, focusing on the groups of people living together with the public consciousness and helping the underprivileged, as well as in need of help (4) Khantithamma, focus on the people who are tolerant of conflicting issues, and open to accepting differences in faith, culture, religion, language, and other values, and (5) Santitham, focusing on the power of peace and jointly addressing the conflict from escalating to violence by opening up space for reconciliation and consultation, this will lead to the coexistence between the groups of people by respecting, praising, and honoring each other. Therefore, “Path of Khruba” is the perfect combination between being a “good person” and a “good citizen” to become a model for the way citizens develops into society.
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.
How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".