We Don’t Share! The Social Representation Approach, Enactivism and the Ground for an Intrinsically Social Psychology
Bibliographic record
Abstract
Wolfgang Wagner is a current and productive advocate of the social representation approach. He developed a version of the theory in which social representations are freed from individual minds and instead conceived of as concerted interactions. These epistemological starting points come very close to the enactive outlook on consensually coordinated actions. Yet Wagner is not radical enough in that he continues to see concerted interaction as an expression of representations that are already shared by the actors constituting a group. In our view, the ubiquitous notion of sharedness—which is also found in studies on social models, cultural patterns, schemas, scenarios, and so forth—is conceptually problematic and reveals a misapprehension of how orchestrated actions come about. Moreover, it obscures a proper understanding of what really constitutes intrinsically social behavior. Enactivism provides a much more consistent epistemology for a psychology that is intrinsically social.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.043 |
| Scholarly communication | 0.011 | 0.025 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".