‘It takes a lot of twisting’: doing research in structurally vulnerable spaces
Bibliographic record
Abstract
Context: Addressing structural vulnerability is an increasing focus for primary care researchers. This work can be demanding in terms of professional skills required and personal capacity and even risk secondary trauma. Few institutions offer specific supports or training for conducting research in this domain. Objective: To inform researcher training and education, this study explored the experiences of researchers conducting participatory research with people experiencing structural vulnerability. Study Design and Analysis: Exploratory qualitative study. Reflexive thematic analysis. The research team comprised experienced (2), midcareer (2) and junior researchers (2) working with structurally vulnerable populations across a range of communities. Setting: Community based researchers from a Canadian academic setting. Population Studied: 15 researchers working with people who have experience of structural vulnerability (homelessness, substance use, trauma) who self-identified: 4 male, 9 female; 5 black, indigenous or persons of colour; 8 senior researchers (PI or Associate professor or higher), 3 mid-experience researchers (early post-doctorate/completing PhD), and 4 junior researchers (working as research assistant/Master’s level). Results: From 4 sequential focus groups and 15 individual interviews, three themes emerged: personal motivation – a source of energy and distress; navigating institutional rules and power structures; supports and training. Participants engaged in research based on personal lived experience or following frontline work experience. This ‘insider’ perspective provided understanding and promoted rapport, to promote trusting relationships with community participants. Circumnavigating institutional policies; paying participants, respecting community customs and expectations at odds with institutional ethics requirements; and responding to timelines set by external bodies, tested researchers’ emotional and moral resources. Participants identified a lack of formal training and support. Help when accessed was ad hoc, often consisting of collegial support. Conclusions: To develop and sustain research with people experiencing structural vulnerability, greater institutional reflexivity and flexibility is required. Formal training for researchers in this field could help to prevent burnout and disillusionment.
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 | 0.120 | 0.105 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.027 | 0.069 |
| Scholarly communication | 0.019 | 0.018 |
| Open science | 0.004 | 0.015 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 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".