Good housekeeping: establishing an operationalisation baseline in the testing of transaction cognition entrepreneurship theory
Bibliographic record
Abstract
A transaction-cognition theory (TCT) has been proposed by (Mitchell 2003, 2001) as the potential foundation for a general theory of entrepreneurship. TCT focuses on the thought processes or cognitions that individuals need in order to create value and achieve superior results. Two central tenets of this theory are that: 1) three sets of knowledge structures, Planning, Promise, and Competition cognitions, are required to create a transaction and sustained transaction streams; and 2) three countervailing sets of knowledge structures, fatalism, refusal, and dependency cognitions limit the ability to complete transactions and achieve superior economic performance. The study explores preliminary measures of fatalism, refusal, and dependency cognitions and their impact on intention to venture. In doing so it provides the first empirical investigation of the TCT countervailing tenet, contributing to the development of the theory.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".