The Conceptual Structure of Social Disputes
Bibliographic record
Abstract
We describe and illustrate a new method of graphically diagramming disputants’ points of view called cognitive-affective mapping. The products of this method—cognitive-affective maps (CAMs)—represent an individual’s concepts and beliefs about a particular subject, such as another individual or group or an issue in dispute. Each of these concepts and beliefs has its own emotional value. The result is a detailed image of a disputant’s complex belief system that can assist in-depth analysis of the ideational sources of the dispute and thereby aid its resolution. We illustrate the method with representations of the beliefs of typical individuals involved in four contemporary disputes of markedly different type: a clash over German housing policy, disagreements between Israelis over the meaning of the Western Wall, contention surrounding exploitation of Canada’s bitumen resources, and the deep dispute between people advocating action on climate change and those skeptical about the reality of the problem.
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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 | 0.015 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.008 | 0.029 |
| Scholarly communication | 0.013 | 0.025 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 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".