The Interactional Community: Emergent Fields of Collective Agency*
Bibliographic record
Abstract
Social interaction is generally regarded as elemental to the notion of community. Within the broader discourse on community, the field-interactional perspective is distinctive in its explicit focus on emergent social processes and community change dynamics. Wilkinson (1970) extended Kaufman’s (1959) early work on the interactional approach through an application of the social field concept to community action. In doing so, Wilkinson (1991) outlined several key linkages between social–symbolic interaction and community agency. Despite these promising beginnings, only a modicum of research has examined the theoretical or philosophical underpinnings of the interactional conception of community. This article explores the symbolic-interactionist tenets undergirding the field-interactional approach, most notably Mead’s (1934, 1938) discussion of generalized social attitudes and Blumer’s (1969a, 1969b) work on joint or collective action.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.037 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".