Blockholder mutual fund participation in private in‐house meetings
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
Abstract The Shenzhen Stock Exchange (SZSE) in China is unique worldwide in requiring disclosure of the timing, participants, and selected content of private in‐house meetings between firm managers and outsider investors. We investigate whether these private meetings benefit hosting firms and their major outside institutional investors—blockholder mutual funds (i.e., funds with ownership ≥5%). Using a large data set of SZSE firms, we find that blockholder mutual funds have more access to private in‐house meetings, and top management is more likely to be present, especially when a meeting is associated with negative news. Furthermore, when blockholder mutual funds attend negative‐news meetings with top management, they are less likely to sell shares, their investment relationship with the hosting firm lasts longer, and hosting firms experience lower postmeeting stock return volatility. These findings suggest that private in‐house meetings are an informative disclosure channel that improves social bonding between top management and blockholder mutual funds in ways that benefit hosting firms.
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 | 0.010 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it