Reclaiming behaviour settings: reviewing empirical applications of Barker’s behaviour settings theory
Bibliographic record
Abstract
Behaviour settings theory is the product of Roger Barker and Herbert F. Wright's decades-long Midwest Field Station research programme. The theory followed from the demonstration that the best predictor of a person's behaviour was the setting (i.e. location, timing and activity) in which their behaviour took place, rather than any individual trait (e.g. personality). Now little known in psychology, behaviour settings theory is often further obscured by being presented as a theory only, neglecting the clear methodology Barker provided for investigating the question: 'What do people do in everyday life?' This literature review takes a comprehensive look at Barker's contributions both within and outside of psychology. The corpus comprises both theoretical and empirical articles; however, our primary interest is in the empirical articles. We describe the who, when and where of behaviour settings research over the past half-century, and we identify branches and neighbours of behaviour settings research (e.g. manning theory, behaviour mapping and activity settings theory). Primarily, however, we attempt to answer the following questions: (i) Are any of Barker's tools for studying people in everyday settings being used currently? (ii) How accurately has Barker's theory been explained, or his methods applied? (iii) Does such work contribute to behaviour settings theory in a meaningful way? This article is part of the theme issue 'People, places, things and communities: expanding behaviour settings theory in the twenty-first century'.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".