Mapping the Collaborative Platform Economy Business Practice
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
This study aims to develop a typological configuration that characterizes the full spectrum of collaborative platform economy business practice in the real world. The analysis is conducted on the basis of a large-scale data set which contains information on 1,335 representative platforms in more than 60 countries on five continents, covering almost all collaborative platform economy business practices mentioned in academic journals and public media. Leveraging the k-means clustering method, an empirical typology comprising seven categories of collaborative platform economy business practice is proposed: collaborative support platform, resource supply platform, authentic C2C platform, C2C mutualized mobility platform, hybrid service platform, B2C service platforms, collaborative finance platform. In addition, with the help of operating status data of the collaborative platform economy, a cross-comparative analysis was also carried out on the category differences and geographic differences.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.040 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.005 |
| 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