Bibliographic record
Abstract
ABSTRACT This paper examines whether risk preferences in the NBA are reference‐dependent and attempts to identify the reference point. Using data from 10 NBA seasons (12,890 games), I find that teams are more likely to attempt a riskier three‐point shot (vs. a less risky two‐point shot) when below the reference point than above it, consistent with Prospect Theory. The results further show that teams are not influenced by a single fixed reference point, but instead, their choices depend on the score difference, most recent score change, and pregame expectations. Additionally, the weight given to the reference point changes over the course of the game. Teams show a breakeven effect, such that they are more likely to attempt a three‐point shot when doing so can tie the game. They also show behavior consistent with mental accounting, as the reference point carries more weight at the end of a quarter than at the beginning. These results provide further real‐world evidence for reference‐dependent risk preferences while highlighting the challenge of applying reference‐dependent models to real‐world settings.
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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 | 0.007 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".