Relying on the engagement of others: A review of the governance choices facing social media platform start-ups
Bibliographic record
Abstract
We are grateful to Professors Rebecca Reuber and Eileen Fischer for contributing our 2022 annual review article. This insightful review explores an issue of great contemporary importance regarding the relationship between entrepreneurial activities and social media platforms. Whilst there is much popular and media commentary regarding the opportunities such platforms offer for entrepreneurship, we lack informed, academic reflection upon the role and influence of such platforms for both good and ill. Hence, this review article is timely in identifying current practices and raising important issues for future research. Our thanks to the authors for their valuable contribution to the ISBJ. Entrepreneurs create digital platforms which, in turn, facilitate entrepreneurial behaviours of others, the platform users. An important start-up activity is developing the mechanisms to govern user participation. While prior literature has provided insights on the governance of innovation platforms and exchange platforms, it has shed little light on the governance of social media platforms. In this review, we synthesize the emerging literature on diverse social media platforms, focussing on four types of governance mechanisms: those that regulate user behaviour, those related to user identification and stature, those that structure relationships among users and those that direct user attention. We highlight the implications of this body of literature for entrepreneurship scholars.
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How this classification was reachedexpand
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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".