The Discursive Frames of Political Psychology
Bibliographic record
Abstract
The aim of this article is to apply elements of contemporary social theory to the major theoretical, methodological, and ideological divisions across political psychology and to consider both the origins and the impact of a range of theories and models. In so doing, we clarify some of the complexity surrounding the discursive and cultural origins of political psychology. On the basis of this analysis, we aim to overcome the redundant binaries and dualisms—both conceptual and geo‐spatial—that have characterized the field up to now. These binary pairs relate to matters of epistemology, ideology, and methodology, and we show how each pair has been the basis of claims made regarding continental differences. As we shall see, such black‐and‐white thinking limits our capacity to understand the nature and potential of political psychology. Instead we wish to encourage a greater degree of universalism and globalism that is appropriate to political psychology as it evolves into a broader global discipline. We argue that political psychology as a field must attempt to deal with the consequences of an increasingly borderless world in which political identities are becoming more fluid, increasingly hybridized, and open to transformation.
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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 | 0.011 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.007 | 0.083 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".