Art for Whose Sake? Managing Professional Autonomy and Empowered Clients in the Porcelain Capital of China
Bibliographic record
Abstract
Existing research suggests that experts often protect their professional autonomy by rejecting lay clients’ feedback or passing it to intermediaries (e.g., managers and agents). However, the rise of review platforms and disintermediated marketplaces has empowered clients to publicly share challenging feedback, and experts’ defensive tactics may further erode public trust in their services. In contrast, our qualitative study of 67 porcelain artists in China reveals that experts can effectively translate clients’ feedback to preserve their professional autonomy. These artists decomposed and distilled their expertise—differentiating the essential, identity-defining aspects from the more-peripheral, expendable ones—allowing them to incorporate clients’ feedback into the latter aspects while retaining control over the former ones. This strategy enabled the artists to integrate client-driven creations into their professional identity as artistic experts, thereby preserving their professional autonomy. Notably, not all artists adopted this strategy. Those who considered their work as an indivisible whole were financially compelled to bend to clients’ demands, or they chose to exit the profession. These findings present a paradoxical view of professional autonomy, suggesting that experts can maintain their professional freedom by granting clients limited and selective influence, thereby fostering clients’ compliance and public recognition in an era of increasing influence by lay audiences.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".