A Comparative Study of Proper Administration of the Non-governmental Organization in the Laws of Iran, Armenia, and Canada
Bibliographic record
Abstract
Non-governmental organizations (NGOs), with their professional and non-political nature, play a fundamental role in promoting sustainable development and supporting the legal demands of citizens. These organizations have been praised for supplying innovative and people-oriented approaches to providing services, support, and empowerment; but in Iranian society, these organizations are in a state of disarray in such a way that they face many challenges in the way of establishment, supervision, financing, and liquidation, which will lead to the weakening of the public sphere. Getting rid of the existing reality and moving towards the desired situation requires the application of standards that can bring positive consequences for nongovernmental organizations. The current research aims to investigate the components of enhancement concerning non-governmental organizations in the laws and regulations of three countries of Iran, Armenia, and Canada. In terms of its descriptive purpose and research method, the current research will be in the form of collecting information through library study and collecting awards and valid legal documents, as well as reviewing and analyzing the content of these documents. The findings of the research show that Armenia has adopted comprehensive laws and regulations to support the activities of non-governmental organizations and has prepared official structures and committees to attend and consult with civil organizations. In addition, by using physical and virtual tools and official processes, it has provided capacities for the participation of NGOs. In Canada, there is no independent law regarding nonprofit organizations and these organizations operate according to the "Non-profit Organizations and Corporations Act". Iran continues to suffer from the lack of a comprehensive law for the activities of non-governmental organizations and there are no strong specific structures to attract the participation of these organizations.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".