Economic Impact Analysis versus Cost Benefit Analysis: The Case of a Medium-Sized Sport Event
Why this work is in the frame
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Bibliographic record
Abstract
This paper empirically illustrates the difference between a standard economic impact analysis (EIA) and a cost-benefit analysis (CBA). The EIA was conducted using an existing (input-output) I-O model (STEAM). The benefit side of the CBA included non-local visitor spending, the revenue of the local organizing committee (LOC), the consumer surplus, and public good value of the sport event for the local residents. The cost side of the CBA was estimated based on the opportunity costs related to the construction of the stadium (including labor costs and the cost of borrowing), imports, and ticket sales to locals. The EIA indicated that the 2005 Pan-American Junior Athletic Championships generated a net increase in economic activity in the city of $5.6 million. The CBA showed a negative net benefit of $2.4 million. Both methods presented challenges and limitations, but CBA has the distinct advantage that it identifies the net benefits associated with hosting a sport event.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it