Bibliographic record
Abstract
This article makes a contribution to the conflict resolution literature by examining the effect of relative hedonic utility on budgetary conflict resolution. A lab experiment, using practicing CPAs as subjects, has been conducted to examine the effect. The literature in this field supports the implication that a person's happiness, which classical economists call hedonic utility, depends not only on the true state she (he) is in, but also on her (his) perceived state relative to the state of others. The biased perception makes a decision maker look at the state of the world more often when the state is bad than when the state is good, according to a prior research study. Although the true state of the world is split evenly between a good state and a bad one, a biased perception makes a decision maker compare herself more often to her neighboring individual when the state is bad. Accordingly, a decision maker who feels unhappy more often, while the magnitude of the pain may be the same, would exhibit a more distributive, zero-sum game type conflict resolution mode relative to another decision maker who feels unhappy less often and shows a more integrative conflict resolution mode. The test results confirmed the hypotheses. Statistically significant test results show that there are distinct effects of biased perception of individuals on budgetary conflict resolution.
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".