The Impact of Ronald Coase’s “Nature of the Firm” on my Research Agenda on Overseas Chinese Merchants in Southeast Asia
Bibliographic record
Abstract
Abstract Ronald Coase (1937), in his article “Nature of the Firm,” argued that if the price mechanism is used, a factor of production (owner of the firm) would need to negotiate a series of contracts separately with each of the factors with whom he is co-operating; these contract negotiation costs could be reduced by organizing a firm because the owner-entrepreneur of the firm is able to direct resources within the firm, hence saving some transaction costs. Furthermore, Coase used a von Thünen concentric circles diagram to depict a single-product firm, as it expands, grows into a multi-product firm. My theory of the ethnically homogeneous [Chinese] middleman group/EHMG (Landa 1981), argued that the EHMG is an organization which reduces the transaction costs of contract enforcement. Using a von Thünen concentric circles diagram, I showed how a rational trader chooses his trading partners, moving from the innermost circle (most trusted partners) outwards to the ethnic boundary as he expands the size of this trading network. The aggregative result of all rational traders’ choice of trading partners is the spontaneous emergence of the EHMG. My 1981 papers together with subsequent published papers on the EHMG have been reprinted in my book, Economic Success of Chinese Merchants in Southeast Asia (Landa 2016); these papers created the “Economics of Identity,” a new subfield, while carrying on the Coasian transaction costs tradition.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.008 | 0.013 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".