Radical uncertainty and pragmatism: Threat perception and response
Bibliographic record
Abstract
Abstract This article brings a pragmatic perspective to the analysis of threat perception in two important ways. First, as does the philosophical tradition of pragmatism, the article joins perception (or knowledge) together with response (action). Perception and response, knowledge and action, are inextricably linked as people learn through the creation of knowledge what is useful in the world. It is in this sense that pragmatists understand the perception and response to threats as evolved practices that are conjoined. Second, the paper explores threat perception and response under the condition of radical uncertainty. I explore the kinds of strategies leaders can use to respond to perceived threat in a context of radical uncertainty, the defining characteristic of contemporary world politics, and explore the advantages of pragmatic strategies that proceed to look for ‘what works in the world’ as provisional responses to perceived threats through iterative, ongoing experimental processes.
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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 | 0.023 | 0.063 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.040 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".