Debriefing can reduce misperceptions of feedback: The case of renewable resource management
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
According to the hypothesis of misperception of feedback, people's poor performance in renewable resource management tasks can be attributed to their general tendency to systematically misperceive the dynamics of bioeconomic systems. The thesis of this article is that dynamic decision performance can be improved by helping individuals develop more accurate mental models of renewable resource systems through training using computer simulation-based interactive learning environments (CSBILEs) that include debriefing. A laboratory experiment is reported in which participants managed a dynamic task by playing the roles of fishing fleet managers. One group of participants used a CSBILE with debriefing, and another group used the same CSBILE but without debriefing. A comprehensive model consisting of four evaluation criteria was developed and used. The evaluation criteria were task performance, structural knowledge, heuristics, and decision time. It was found that debriefing was effective on all four criteria: Debriefing improved task performance, helped users learn more about the decision domain and develop heuristics, and reduced decision time in dynamic decision making.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it