Practical poststructuralism for confronting wicked problems
Bibliographic record
Abstract
This paper discusses an innovative qualitative-quantitative modelling method relevant to two characteristics of wicked problems: they have no definitive formulation, and the choice of how they are defined or explained determines the nature of their resolution. Through projects conceptualizing the human dimensions of climate change, the socio-technical dynamics of the Energiewende (Germany’s low-carbon energy transition), and of water futures of a megacity (Lima), it has been found that the system-theoretic method of cross-impact balances (CIB) reveals fundamental assumptions in interdisciplinary modelling projects and opens them up for investigation. This can democratize modelling exercises while preserving scientific credibility. It can also enhance mutual learning across collaborators and study participants by interrogating the processes, collaborators, methods, or participants that appear to have epistemic authority at different stages of the project and whether such authority is justified. Through these capabilities, CIB gives new practical relevance to deconstructive, critical practices that characterize modes of thought from the humanities and social sciences—namely poststructuralism—and brings new reflexivity to modelling studies.
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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 | 0.058 | 0.079 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.009 | 0.115 |
| Scholarly communication | 0.011 | 0.025 |
| Open science | 0.004 | 0.018 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".