Концептуализация правительски-организованных неправительственных организаций (Conceptualizing Government-Organized Non-Governmental Organizations)
Bibliographic record
Abstract
The English version of this paper can be found at: https://ssrn.com/abstract=2814215. Russian Abstract: В данной статье предлагается концептуальная основа для определения и анализа современного поведения парадоксальной неправительственной организации, организованной правительством (правительски-организованных неправительственных организаций - ПОНПО). Обсуждается, как деятельность ПОНПО вписывается в основные теории и традиции гражданского общества. Кроме того, наведено сравнение и анализ ПОНПО и неправительственных организаций с точки зрения их источников власти, основных видов деятельности и функций, а также дилемм. Наконец, теоритизируется влияние и последствия роста ПОНПО на отношения между государством и обществом в глобальном масштабе. English Abstract: This article offers a conceptual framework to identify and analyze the contemporary behavior of the paradoxical government-organized, non-governmental organization (GONGO). We discuss how GONGOs’ activities fit within mainstream civil society theories and traditions. Furthermore, we compare and analyze GONGOs and NGOs in terms of their sources of power, main activities and functions, and dilemmas. Finally, we theorize the effects, and implications, the growth of GONGOs has on state and society relations globally.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.014 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".