Culture at the Center of Economic Development, Stability and Growth
Bibliographic record
Abstract
<p>This paper stresses the importance of culture in understanding and, perhaps more accurately, predicting economic development. It’s intended to initiate, or re-initiate, the discussion of culture as the core of economic development, stability and growth.</p><p>My interest in the discussion of the economy is from a behavioral perspective, taking behavior as an outcome of culture, a factor that remains neglected in most economic literature explaining or forecasting the economy. It seems to me that because the existent literature in economics remains incomplete in terms of culture, predicting the success or failure of any economic model, applied within different cultural settings, may be inaccurate. Hence, the fundamental assumption presented in this document is that different regions in the world develop different economic levels due to cultural differences. I take example in East Asia in general and China in particular to explain cultural factors that have contributed to the economic development in the region.</p><p>The following discussion has been divided into five parts, as follows: First, an introduction to the main arguments. Second, a short discussion of the definition of culture developed by several scholars in the past. Elaborating on those earlier definitions, I propose a definition that may best suit the economic issue at hand. Third, a review of some of the most important economists and their key arguments, upon which I elaborate from a cultural perspective. Fourth, a discussion of East-Asian countries and China’s economic development from a cultural perspective. Fifth, my conclusions and a proposed model that includes culture as a factor in the decision-making process when choosing an economic strategy and its corresponding models.</p>
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".