1 AFFORDANCE AND BEHAVIOR SETTING: A MULTI-LEVEL ECOLOGICAL PERSPECTIVE IN THE STUDY OF THE MEANING OF HABITAT
Bibliographic record
Abstract
Habitat, the environment where people dwell and have their everyday life and activities, has characteristics and features that afford opportunities for social practices and actions, and that communicate meanings.Individuals and collectives, through these social practices and activities, assign meanings to habitat.The relationship between habitat and individuals is thus mutual.But there is no consensus as to how the fit between environments and individuals works.In other words, what is the congruence between people and habitats made of and how can it be studied, and what happens when features of the environment and/or characteristics of people are shaped or changed?This paper proposes a conceptual framework using Barker's concept of behavior setting and Gibson's notion of affordance for the study of habitat and its meanings.Habitat can be conceptualized as consisting of several behavior settings (BS).A BS is a higher order environmental structure which is suited to certain behavior patterns.But we question the limits of two important facets of a BS: being a function of collective action alone and being relatively stable in space and time.Environments are used and (re)shaped constantly by participants and other stakeholders.Considering a BS only as a relatively static environmental structure would limit the understanding of the complex mutual relations between the setting and the social practices that occur in it.At the same time, the collective focus of a BS limits the preciseness of the description of its milieu properties for understanding their congruence with the participants.Approaching a behavior setting with affordances in mind can lead one to think about the kind of individuals who would participate in particular settings.Affordances, by definition, are identified relative to the actions of specific perceivers.If affordances are socio-cultural phenomena then shared functional characteristics of the participants in the setting might be considered for understanding the nature of a behavior setting.This means that the functional characteristics of a behavior setting may be specified relative to the shared or normative characteristics of a group of participants or intended users, who are often also individually motivated by the affordances provided by the BS to participate in the setting.In this paper, a conceptual framework for studying habitat from a multi-level ecological perspective will be further elaborated.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.020 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".