Volume 2: Development Models in Muslim Contexts : Chinese, 'Islamic' and Neo-liberal Alternatives
Bibliographic record
Abstract
Recent discussions of the 'Chinese economic development model', the emergence of an alternative 'Muslim model' over the past quarter century and the faltering globalisation of the 'Washington Consensus' all point to the need to investigate more systematically the nature of these models and their competitive attractions. This is especially the case in the Muslim world which both spans different economic and geographic categories and is itself the progenitor of a development model. The 'Chinese model' has attracted the greatest attention in step with that country's phenomenal growth and therefore provides the primary focus for this book. This volume examines the characteristics of this model and its reception in two major regions of the world - Africa and Latin America. It also investigates the current competition over development models across Muslim contexts. The question of which model or models, if any, will guide development in Muslim majority countries is vital not only for them, but for the world as a whole. This is the first political economy study to address this vital question as well as the closely related issue of the centrality of governance to development.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".