Brief of Professors at Law and Business Schools As Amicus Curiae in Support of Respondents, Leidos, Inc., fka SAIC, Inc., Petitioners, v. Indiana Public Retirement System, Indiana State Teachers’ Retirement Fund, and Indiana Public Employees’ Retirement Fund, Respondents, No. 16-581 (S. Ct. Sept. 7, 2017)
Bibliographic record
Abstract
This Amicus Brief was filed with the U.S. Supreme Court on behalf of nearly 50 law and business faculty in the United States and Canada who have a common interest in ensuring a proper interpretation of the statutory securities regulation framework put in place by the U.S. Congress. Specifically, all amici agree that Item 303 of the Securities and Exchange Commission's Regulation S-K creates a duty to disclose for purposes of Rule 10b-5(b) under the Securities Exchange Act of 1934.\nThe Court’s affirmation of a duty to disclose would have little effect on existing practice. Under the current state of the law, investors can and do bring fraud claims for nondisclosure of required information by public companies. Thus, affirming the existence of a duty to disclose will not significantly alter existing practices or create a new avenue for litigants that will lead to “massive liability” or widespread enforcement of “technical reporting violations.”\nAt the same time, the failure to find a duty to disclose in these circumstances will hinder enforcement of the system of mandatory reporting applicable to public companies and weaken compliance. Reversal of the lower court would reduce incentives to comply with the requirements mandated by the system of periodic reporting. Enforcement under Section 10(b) of and Rule 10b-5(b) under the Securities Exchange Act of 1934 by investors in the case of nondisclosure will effectively be eliminated. Reversal would likewise reduce the tools available to the Securities and Exchange Commission to ensure compliance with the system of periodic reporting. In an environment of diminished enforcement, reporting companies could perceive their disclosure obligations less as a mandate than as a series of options. Required disclosure would more often become a matter of strategy, with issuers weighing the obligation to disclose against the likelihood of detection and the reduced risk of enforcement.\nUnder this approach, investors would not make investment decisions on the basis of “true and accurate corporate reporting. . . .” They would operate under the “predictable inference” that reports included the disclosure mandated by the rules and regulations of the Securities and Exchange Commission. Particularly where officers certified the accuracy and completeness of the information provided in the reports, investors would have an explicit basis for the assumption. They would therefore believe that omitted transactions, uncertainties, and trends otherwise required to be disclosed had not occurred or did not exist. Trust in the integrity of the public disclosure system would decline.\nThe lower court correctly recognized that the mandatory disclosure requirements contained in Item 303 gave rise to a duty to disclose and that the omission of material trends and uncertainties could mislead investors. The decision below should be affirmed.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.017 | 0.012 |
| Insufficient payload (model declined to judge) | 0.077 | 0.035 |
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".