Three Identity Principles at the Core of Comparative Economic Development Management: Lessons for Emerging African Nations
Bibliographic record
Abstract
The aim of this article is to investigate the role of national or social identity at different stages of the industrialized nations’ economic development models in order to draw some actionable lessons for emerging markets and developing African economies. The main assumption is that social identity is at the core of the economic management process industrialized nations implement with regard to achieving sustainable development goals. In order to detect actionable information with practical or methodological relevance, national identity was identified as the independent variable, and economic development as the dependent variable. Although the concept of identity is diversely defined in scholarly literature, it is commonly understood as the lens through which an individual perceives himself/herself or how a group of individuals perceive themselves, and their role in finding a way to cope with environmental challenges. Therefore, there is a double level of identity: at the individual level, and collectively as a nation. This identity is at the core of social reflexivity, which is used to envision, manage, and structure the institutional actions that are conducive to economic development. National and international development agencies have been experimenting with different models to achieve economic development in the emerging countries since the creation of the Bretton Woods Institutions at the end of the Second World War. The Millennium Development Goals (MDG) of the United Nations remain the last major multilateral management framework in a series of trial-and-errors over the last sixty years. Using an exploratory and descriptive approach, this article systematically compares the core of the economic development models of the Western nations and that of the newly emerging countries. The results of this analysis show that to achieve their economic development goals, industrialized and emerging countries built the managerial core of their development models on three major foundations: a political system that stems from their own idiosyncrasies, a belief system that comes from their own history and traditions, and a unique but non-exclusive mode of production and resource allocation. These three pillars form a tryptic management principle of sustainable economic development ready for adaptation and adoption.
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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 | 0.019 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.009 | 0.032 |
| Scholarly communication | 0.011 | 0.022 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| 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".