The VOICES Typology of Curatorial Decisions in Narrative Collections of the Lived Experiences of Mental Health Service Use, Recovery, or Madness: Qualitative Study
Bibliographic record
Abstract
BACKGROUND: Collections of lived experience narratives are increasingly used in health research and medical practice. However, there is limited research with respect to the decision-making processes involved in curating narrative collections and the work that curators do as they build and publish collections. OBJECTIVE: This study aims to develop a typology of curatorial decisions involved in curating narrative collections presenting lived experiences of mental health service use, recovery, or madness and to document approaches selected by curators in relation to identified curatorial decisions. METHODS: A preliminary typology was developed by synthesizing the results of a systematic review with insights gained through an iterative consultation with an experienced curator of multiple recovery narrative collections. The preliminary typology informed the topic guide for semistructured interviews with a maximum variation sample of 30 curators from 7 different countries. All participants had the experience of curating narrative collections of the lived experiences of mental health service use, recovery, or madness. A multidisciplinary team conducted thematic analysis through constant comparison. RESULTS: The final typology identified 6 themes, collectively referred to as VOICES, which stands for values and motivations, organization, inclusion and exclusion, control and collaboration, ethics and legal, and safety and well-being. A total of 26 subthemes related to curation decisions were identified. CONCLUSIONS: The VOICES typology identifies the key decisions to consider when curating narrative collections about the lived experiences of mental health service use, recovery, or madness. It might be used as a theoretical basis for a good practice resource to support curators in their efforts to balance the challenges and sometimes conflicting imperatives involved in collecting, organizing, and sharing narratives. Future research might seek to document the use of such a tool by curators and hence examine how best to use VOICES to support decision making.
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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 | 0.093 | 0.137 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.019 | 0.031 |
| Scholarly communication | 0.014 | 0.021 |
| Open science | 0.005 | 0.020 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".