The Key-Attributes That Influence the Fans’ Perceptions of the Corinthians’ Ecosystem
Bibliographic record
Abstract
Objective: This article aims to understand and analyse which fans’ attributes most infers in their view concerning the sports ecosystem of the Sport Club Corinthians for sporting events. Methodology: an exploratory research was carried out consisting 78 topics using the Likert scale to be administered to 180 sports fans in 3 matches between February and March 2017. The analysis procedure followed three steps: (i) calculating the chi-square testes cross tables; (ii) selecting the topics which achieved less than 5% significance; (iii) and identifying that group of fans’ attributes that are most similar and most divergent. Findings: monthly salary is the most critical fan attribute; monthly attendance is the second fan attribute most divergent. Fans understand that the stadium as well as partnerships and sponsorships as the critical dimensions of the Corinthians’ ecosystem. Conclusion: Therefore, 2 out of 3 hypotheses were confirmed. Besides, issue as to gender is not a critical fans’ attributes for the Corinthians’ marketers.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".