The Enigma of an Emerging Pink Economy in China: Pain Points, Entrepreneurial Opportunities, and Organizational Legitimacy<sup>1</sup>
Bibliographic record
Abstract
This article examines why an aboveground pink economy has emerged in mainland China, where equal rights for gay people are repressed and public attitudes toward homosexuality are overwhelmingly negative. Drawing on interviews, supplemented with a minimal amount of media data, this article demonstrates that in China there was a group of gay people wishing to fulfill needs mainstream businesses disregard and that such consumer needs necessitate China’s pink sector. More importantly, the state set the stage for the nascent sector to emerge: Government policies triggered a surge in funding resources and technology infrastructure upgrades that laid the material foundations for pink entrepreneurship. Despite being born in an institutional void, pink ventures employed legitimizing strategies to hedge against risk and uncertainty, thereby consolidating this new market. China’s pink economy developed independently of the influence of the gay movement and even expanded, as never before, at the low ebb of the movement. This research gives credence to the notion that an aboveground pink economy could precede political rights but, unlike American scholarship, questions a similar causal relationship between the two in the Chinese context.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.014 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".