Non-public contracts, cash flows and firm value: the case of Lockheed
Bibliographic record
Abstract
Purpose – This study aims to examine a large, non-disclosed production contract awarded to Lockheed Corp. in the context of a trade-off between a contractually required non-disclosure clause and the need (as a publicly traded firm) to disclose material information to its shareholders. This production contract generated significant cash flows to the firm as evidenced by growth in its earnings. However, the existence of the production contract and its contribution to Lockheed’s earnings, was not disclosed by the firm to shareholders and potential investors while the production contract was being executed. Design/methodology/approach – The authors examine the market reaction to several key contract events which were not disclosed at the time they occurred, in compliance with the contractually required non-disclosure clause. Findings – A statistically significant stock price reaction around the time of the award of this non-public contract, indicative of trading by some capital market participants using non-public information was documented. Originality/value – Because similar large non-public contracts funded by the government are common in the industrial economy, we conclude by discussing implications for organizational structure, firm’s cost of capital, equity-based compensation and market efficiency.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".