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.
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.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".