Communicative action in practice: Future Search and the pursuit of an open, critical and non‐coercive large‐group process
Bibliographic record
Abstract
Abstract Future Search has emerged as a widely used large‐group process for building common ground and stimulating multi‐stakeholder action on complex issues in a collaborative and participatory way. Yet there are few careful evaluations of the approach. Through a detailed qualitative analysis, this paper critically assesses a Future Search conference on repetitive strain injuries (RSI) held in 1998. The paper draws on Jürgen Habermas' standards of communicative action to explore the extent to which the process was inclusive, non‐coercive and reflective. The Future Search process encouraged participants to introduce a variety of observations, beliefs and experiences. Two fundamentally opposed analyses of RSI arose: a ‘consensus–knowledge’ model and a ‘conflict–power’ model. However, the process fell short of communicative action because its structure privileged—and thus led to the uncritical adoption of—the former model without allowing adequate participant reflection on the questionable and contested assumptions upon which the model is based. Copyright © 2002 John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.061 | 0.102 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.013 | 0.072 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.006 | 0.004 |
| 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".