Beyond <i>Moneyball</i> to social capital inside and out: The value of differentiated workforce experience ties to performance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The differential impact of social capital among employees in strategic and support roles has received far less attention than that of human capital in talent management literature. Building on network closure theory and differentiated workforce theory, we examine the effect of strategic and support teams’ experience ties on team performance while controlling for human capital using current Moneyball ‐inspired metrics for workforce quality. Using an 111‐year longitudinal data set of 15,837 Major League Baseball players from all 30 teams and 3,475,778 experience ties, we find that after accounting for the effect of team quality, managerial stability and reputation, and era effects, organizational experience ties and subsequent team performance have an inverted U‐shaped relationship for strategic roles and a U‐shaped relationship for support roles. Competitor experience ties have an inverted U‐shaped relationship on performance for strategic roles, yet the hypothesized U‐shaped relationship showed differences for different competency areas among support roles. This study highlights the value of social capital to team performance and the importance of differentiating human resource management (HRM) practices for strategic and support roles in 20 different competency areas. It also showcases how workforce analytics with big data can be applied to HRM and have value added impact on workforce and firm strategy execution.
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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 | 0.000 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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