Timeline Mapping in Qualitative Interviews: A Study of Resilience with Marginalized Groups
Bibliographic record
Abstract
Growing interest in visual timeline methods signals a need for critical engagement. Drawing on critical emancipatory epistemologies in our study exploring resilience among marginalized groups, we investigate how the creation of visual timelines informs verbal semistructured interviewing. We consider both how experiences of drawing timelines and how the role of the timeline in interviews varied for South Asian immigrant women who experienced domestic violence, and street-involved youth who experienced prior or recent violent victimization. Here we focus on three overarching themes developed through analysis of timelines: (a) rapport building, (b) participants as navigators, and (c) therapeutic moments and positive closure. In the discussion, we engage with the potential of visual timelines to supplement and situate semistructured interviewing, and illustrate how the framing of research is central to whether that research maintains a critical emancipatory orientation.
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 | 0.047 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.015 | 0.027 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.003 | 0.004 |
| 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".