Competitive Rationales: Beneath the Surface of Competitive Behavior
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
Competitive dynamics research has focused on studying whether rivals are able and likely to carry out competitive actions, typically by examining indirect reasons such as characteristics of the actions themselves, the firms involved, or the competitive context. We explore why rivals initiate a specific competitive action at a particular time and situation. Drawing from the philosophy of action literature, we introduce the concept of competitive rationales to examine the primary reasons that cause tactical actions. Given the rapid exchanges characterizing tactical competitive dynamics, we conducted an inductive, multicase study to explore the reasons behind over 800 discrete tactical decisions carried out by 9 professional basketball coaches during 15 basketball games. To garner insight, we develop a conceptual framework revealing their types and scope. Even during intense head-to-head rivalry, most rationales were not rivalrous but were instead organizational-to optimize resource use, strategic consistency, and reputation-or social-to manage relationships. Moreover, the three main types of rationales varied in scope, extending beyond immediate competitive situations and rivals to address longer term, strategic outcomes, and assorted stakeholders. Thus, our analysis reveals these rationales to be complex and potentially difficult for rivals to decipher. It also recasts each component of the dominant awareness-motivation-capability (AMC) model of rivalry, suggesting that awareness is challenged by subtle rationales, motivation drives not only action but also forbearance, and capability is both a requirement and product of action.
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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 it