Bibliographic record
Abstract
Purpose Since the 1990s, most bilateral and supranational donor agencies have been pursuing “good governance” as their priority development policy. Yet, in their own evaluation, the speed of progress of this gargantuan governance project has remained unsatisfactory. The purpose of this paper is to examine the causes of this slow progress by scrutinizing its conceptual foundation. Design/methodology/approach The analytical approach of this paper is purely speculative, which is occasionally supported by real world data and socio‐political evidences. Since the paper usesGovernance for Sustainable Human Development – A UNDP Policy Documentas the ruling reference material, the paper has been so titled. Findings First, defining governance as a process misrepresents its problematic nature, which is primarily political and therefore diverts world attention from its root‐causes. Second, governance literature treats the state and government as synonymous and by that confuses their political nature. Finally, the paper assigns an all‐impressing role to civil society organizations (CSOs) in promoting good governance in the developing world. However, experience shows that they are deeply involved in the creation and continuation of poor governance in the developing country. Practical implications Humankind now lives in a global village divided into territorially demarcated political units. Accordingly, the peace and prosperity of the global village critically depend upon how democratically each of member state is governed. Good governance in turn hinges on politically trained intelligent and ethical individuals running public administration. The analytical opinions of the paper underline this notion. Originality/value The paper shows that the ongoing development discourse on good governance revolves around a faulty conceptual foundation. By reviewing the major ideas of the governance paradigm, it clarifies the conceptual connections between political theories and democratic governance.
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 | 0.015 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.034 | 0.014 |
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".