Good Governance According to Nahjolbalaghe Context
Bibliographic record
Abstract
Good Governance has a long history of human thought and has proposed in the works of various thinkers. By examining the different theories, we are going the government agency, Required for sure non-infringement any community of human beings. The thought of Imam Ali also how the rule and governance in an appropriate manner, has been attending. This article has been extracted from Research on noble Nahjolbalaghe and to assess components of governance had paid from the sight of Imam Ali. Using content analysis, Statements related to governance derived from Nahjolbalaghe and then encrypt the data and using the software SPSS, the data have been analyzing. The final study Extraction and compilation of eleven components: The rule of law, Justice, and Anti-oppression, equality, participation, Self-regulatory Instead of monitoring people, preparing the groundwork to move people toward God, Clarifying public opinion, preparation for a healthy and dynamic economy, manage life’s value of a poor class of Society, Social security and accountability to God and the people. These are Indicators that Imam Ali believed are required for "Good governance" in the 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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".