Information Signal Quality and Risky Project Evaluation in Organizations (Environment, Adoptability and Choice–Hierarchies and Polyarchies)
Bibliographic record
Abstract
In this paper, risky project evaluation in organizations is modelled in a linear information signal framework, which enables the following multidimensional analysis: “Ability”–Agents may have different abilities in processing information for risky project evaluation; “Endogenity”–It is possible to choose the organization type internally, or the organization type may be determined externally by the environment, in which case it is necessary for the evaluation criteria to adopt to the environment; “Sensitivity”–Risky and risk-free alternatives may not necessarily be equal with positive risk sensitivity and positive price of risk; “Project Quality”–The project quality may always be a certain type, for example, fixed (below or above average all the time) or it may be variable, which may affect the evaluation criteria; “Communication”–Communication between the agents may be in an information quality improving or detoriorating manner; “Coordination”–There may be an existance problem for the organization (it may exist due to an external setup, or from internal dynamics), and there may be a need for coordination between the agents in case it exists with internal dynamics. Risky project evaluation in organizations with a specific information signal quality has not been analyzed in the literature before and is a contribution of this paper. As a result of the analysis, most of the multidimensional variables mentioned in organizational decision making are original and specific to our paper. The results of the analysis have policy implications in all types of organizational settings of collective decision-making environments like family, firm, government, education, military, politics, and economic systems.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".