Legally-informed information disclosure in early-stage ventures
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
Entrepreneurs face unique challenges during the formation of new ventures, including how to balance the tension between sharing and protecting confidential information with potential investors and customers while also ensuring the effective development of these relationships. To address this challenge, we suggest that new ventures employ the concept of legally-informed information disclosure (LID). We define LID as the sharing of sensitive and valuable information through means that, with the legal and relational environments in mind, clearly indicate its value and confidential nature before and during the process of disclosure. This conceptual paper argues that LID lies at the intersection of relational governance, contractual governance, and the legal perspective of breach of confidence. We propose a theoretical framework to illustrate this three-way relationship. Introducing the legal perspective to an established body of literature allows for an actionable framework that is inter-disciplinary, and legally and theoretically supported.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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