Status Games: Market Driving through Social Influence in the U.S. Wine Industry
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
Research on market orientation finds that market-driven firms succeed by identifying and appealing to consumer needs. Yet many technologically innovative firms achieve remarkable success by taking a market-driving approach. The ways that firms drive markets without disruptive innovation, however, remain unclear. Adopting a market-systems perspective, the authors conduct an ethnographic analysis of producers, distributors, retailers, critics, and consumers in the U.S. wine market. They find that firms drive the market by playing a status game. Firms pursue a vision and advance that vision among influencers inside and outside the industry to gain recognition. Winners of the status game influence and drive social consensus by setting benchmarks and shaping consumer preferences to the firm's advantage. High status is difficult to imitate, creating an advantage that can endure for years or decades.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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