Investor Behavioral Anomalies in Wartime Uncertainty: The Case of North Kivu in DRC
Bibliographic record
Abstract
After combining the CPT1, SARF2, and greed and grievances dynamical systems, and the overreactions models, we conducted a questionnaire survey with a sample of 921 investors from North Kivu in the DRC, of which 879 (95%) were in the service sector. The evaluation of the risk taken by investors is carried out at two levels. At the first level, it is assessed according to an informational asymmetry focused on estimating probabilities describing the outlook for results over three years (from 2014 to 2016). At the second level, the analysis describes the investors’ attitude regarding their level of profit expectation as an endogenous variable of heuristic optimization, cognitive bias, and self-expressive bias. The results show that the anomalies described in the interactive behavior of N-K investors during wartime uncertainty stem from a plurality of attitudes reflecting an ambiguity of choices dominated by a sub-reaction at the base of reluctance and a loss of opportunity in the market.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".