Using Contextual Action Theory and Action-Project Method to Study Real-Time Identity
Bibliographic record
Abstract
This conceptual paper describes how Contextual Action Theory and its associated methodology, the Action-Project Method, can be used to study real-time identity processes as they are embedded in identity construction over time. Contextual Action Theory is a conceptual framework based on the view that human action is goal-directed. In this view, identity construction is conceptualized as a series of goal-directed actions over an extended period of time. Within that series of actions are the specific real-time identity processes defined as everyday activities as people engage together. These real-time processes operate as building blocks of identity construction. The Action-Project Method is a comprehensive protocol for conducting longitudinal qualitative research. Goal-directed actions are considered through three interacting dimensions: (a) levels of action, (b) perspectives on action, and (c) action systems. The Action-Project method is designed to collect data from the three perspectives on action: manifest action, internal processes, and social meaning. The description of the theory and method in relation to identity construction is followed by two case illustrations. The first case illustration demonstrates the use of the theory and method with two socially-related young adult participants. The second case illustration involves a counselor and a young adult participant.
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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 | 0.027 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.005 | 0.017 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".