Shared economy development model with economic development approach in Iran's sports industry
Bibliographic record
Abstract
This study aimed to develop a model for developing a shared economy with an economic development approach in the Iranian sports industry. The research method was a two-stage exploratory combination of instrument making. In the qualitative part, the purposeful sampling method and theoretical saturation technique were performed. The tools used were to identify semi-structured interviews (with focus groups) and study documents. To ensure the validity and reliability of the study, the Lincoln and Guba evaluation methods were used. In the quantitative part, the research method was a descriptive survey. The statistical population was the economic activists in sports and sports marketing students. According to Cochran’s sample size determination formula, 384 people were considered as the sample. to collect data from the questionnaire of the framework model of the shared economy model in sports with an economic development approach that includes 43 items that have been extracted according to the theoretical foundations and the qualitative part of the research. Eight professors of sports management were used to evaluate the face validity and the carcass model was used for the content validity of the questionnaire questions. (CVR=0.86) and content validity was confirmed. Cronbach's approved alpha was also used. Descriptive statistics and structural equation modeling were used to analyze the data to evaluate the fit of the research model. The results of the research in the qualitative section showed that after examining the Delphi method and performing the first stage, 31 items were identified. In the second stage, 40 items were identified, and in the third stage; Finally, 50 items were identified. The three dimensions of human ecology, fiscal policy, and value-oriented processes emerged as a framework for the model of a shared economy in sports with an economic development approach. And in the quantitative part, the human ecology dimension with a value of 0.71 affects the value-oriented process dimension with a value of 0.65 and the fiscal policy dimension with a value of 0.63 affects the framework for the development of a shared economy in sport. The results also showed that the research model has a good fit. Therefore, it is suggested that the sports organizations' managers pay attention to the factors of this research to implement economic development by emphasizing a shared economy.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".