The New Normalcy and the Pandemic Threat: A Real Option Approach
Bibliographic record
Abstract
This paper delves into the evolving post-pandemic business arena, focusing on how liability options and social norms are reshaping industry structures. We anticipate lasting transformations due to the emergence of new safety standards that bridge the gap between corporate interests and societal welfare. To foster these changes, effective post-lockdown economic policies could encompass not only rigorous social standards but also specific financial incentives. Examples of such incentives include tax relief for businesses implementing comprehensive health protocols and subsidies for those transitioning to remote work or modifying production layouts to minimize infection risks. Our analysis delineates two predominant operational frameworks for firms in this new environment: the liability and property regimes. These are determined by each firm’s financial outcomes and the extent of damages incurred, all measured against societal expectations. Firms within the liability regime may exhibit only partial compliance, often attributed to ambiguous standards and prevailing uncertainties, potentially leading to a dip in profits. In contrast, entities operating under the property regime are likely to engage in more extensive organizational restructuring. A key insight from our study is the paradigm shift in investment behavior, increasingly influenced by risk management, particularly in the strategic choice between liability and property rules. This shift is evident in how firms now prioritize managing potential external liabilities, such as environmental hazards or evolving regulatory landscapes, in their investment decisions. Consequently, the traditional growth-centric investment paradigm is being supplemented by strategies that emphasize safeguarding against various external risks, marking a significant realignment in corporate investment philosophies post-pandemic. This transition underscores the intricate interplay between economic policies, corporate strategies, and societal dynamics in the contemporary business milieu.
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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 | 0.001 | 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 | 0.000 |
| 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".