The effects of health, social, and consumption capital on running-related expenditures in China
Why this work is in the frame
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Bibliographic record
Abstract
Research question: This study investigates the effects of health, social, and consumption capital on running-related expenditures. It adds to previous research by empirically testing investment in the stock of health on participation-related expenditures.Research methods: Chinese amateur runners (n=6,693) were surveyed on health capital (i.e. health change since taking up running), social capital (i.e. running group participation), consumption capital (i.e. sport profiles), socio-demographics, and running-related expenditures over a one-year period. Two instrumental variables reflecting life domain satisfaction were included to address the endogeneity of health change.Results and findings: Results show that variables capturing health, social, and consumption capital significantly affect total running-related expenditures, whereas the effects on expenditure categories vary. After taking endogeneity into account, the results show that health change since taking up running positively affects total running-related expenditures and sport apparel expenses.Implications: The findings provide empirical support for Downward et al.’s (2009) general economic model of sports consumption by revealing that health, social, and consumption capital are significant drivers of participation-related expenditures. While mass participation, health, and economic objectives may be achieved concurrently, policy makers should carefully balance these objectives. Sport managers and marketers can use mass participant sport events to stimulate continued participation, and this in turn generates health, social, and consumption capital that drives expenditures. Fostering running group participation increases expenditures. Early career runners should be targeted for sport apparel. Cross-promotion among related sports may increase overall sport consumption.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it