Bibliographic record
Abstract
Peter J. Balint, Ronald E. Stewart, Anand Desai and Lawrence C. Walters Wicked Environmental Problems: Managing Uncertainty and Conflict Washington, DC: Island Press, 2011Reviewed by Michael W. PopejoyWe all know about problems, and the various definitions of problems: complex problems, critical problems, intractable problems, problems with rational solutions, and problems that resist rational In the field of public health, we grapple with social problems that cause poor health outcomes such as lack of education, poverty, illiteracy, lack of access to health care facilities, etc.Yet, here comes a more recent; and more complicated order of problems called And, by wicked, the meaning is clear when we examine the characteristics of this category of problems. Wicked problems resist rational solutions; indeed, it is possible that truly wicked problems have no solution whatsoever that will satisfy everyone that are affected by the problem under study. Obviously, those people who solve problems and those people are affected by problems certainly resist hearing that any problem is most likely irresolvable.A wicked problem is characterized by a high degree of scientific uncertainty and deep disagreement on values. (p. 2). Consequently, there is no single, correct, optimal solution. So, in effect, wicked problems have no single best solution which can be a cause for concern for many whose job it is to solve social and environmental problems. When scientific uncertainty meets profound differences in perceptions, attitudes, and values of the key stakeholders, we have problems that any solution will be almost impossible to satisfy everyone involved.Many, if not all, social problems possess a high level of complexity and social conflict. The usual method of problem structuring and analysis fail to help us arrive at a solution; thus the reliance on technical analysis alone is not possible. Problems take on a complexity that often extends well beyond the merely intricate and assumes many forms, including high levels of risk; scientific uncertainty; biological complexity; social complexity; vast scope and scale of issues involved; and the absence of a clear public consensus on values, the nature of the problem, or acceptable solutions. (p. 9). When the relationship between an action and its outcome is clear, we have a programmed decision; and this poses few problems in implementation since the science is clear and the values are well established and widely agreed upon. Such is not for the wicked problem.The authors provide the readers with a ten point set of characteristics by which to identify the wicked problem: there is no definitive formulation of the wicked problem; wicked problems have no stopping rule; solutions are not true or false, but good or bad or satisfying or good enough; there is no immediate and no ultimate test of a solution; there is no opportunity to learn by trial and error (it is a one shot operation); they do not have a set of potential solutions; every wicked problem is essentially unique; every wicked problem can be considered a symptom of another problem; the existence of a discrepancy representing a wicked problem can be explained in numerous ways; the planner has no right to be wrong (p. …
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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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".