Pragmatic Identity Analysis as a Qualitative Interview Technique
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this article, we examine a qualitative interview and analytical technique for exploring the influences of identities on an individual's experiences. The technique, pragmatic identity analysis (PIA), relies upon a collaborative, reflective, contextually oriented, and relational approach to interviewing. For the purposes of this technique, "identity" is understood as a unique collection of dynamic identities that manifest in diverse contexts. Through narrative dialogue the interview pair jointly reflects upon the identities of the interviewee. They then analyze how identities play a role in the individual's experiences and the formation of values, dispositions towards enacting values, and the sense of wellbeing in different contexts. To examine the efficacy of the technique we present a case study of a first year teacher's growing awareness of her identities and the influence of her identities on her transition to a teaching role.
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.
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 | 0.022 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.012 |
| Science and technology studies | 0.058 | 0.037 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.010 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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 it