From Confusion to Fusion: A New Organizational Form and the Evaluation of Category Spanning in an Established Form
Bibliographic record
Abstract
We investigate how an overall change in audience preferences for category spanning occurs by examining the role of new organizational forms. We suggest that a new organizational form that emphasizes category spanning in its products can enhance evaluations of category spanners in an established form. By promoting an alternative theory of value, the new form helps disrupt existing evaluative frameworks for the established form and shifts audience preferences toward spanning. Using the rise of gourmet food trucks in the U.S. restaurant industry, we analyze Yelp ratings and find an increase in returns to spanning by brick-and-mortar restaurants with the prevalence of gourmet food trucks in the same metropolitan area. A preregistered vignette experiment in the restaurant context provides additional evidence consistent with our argument. We contribute to research on category dynamics and organizational forms by investigating how outsiders influence audience evaluations of spanning, revealing how a new form can heterogeneously affect organizations within an established form. By employing a mixed methods approach that integrates qualitative, statistical, and experimental techniques, this study also makes a methodological contribution.
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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 | 0.012 | 0.051 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".