A Framework for Person-Centred Recordkeeping Drawn through the Lens of Out-of-Home Child-Care Contexts
Bibliographic record
Abstract
This article examines the concept of co-created and person-centred recordkeeping and the needs for this in out-of-home child-care contexts, drawing out a recordkeeping framework. The article uses the research of the UK MIRRA (Memory – Identity – Rights in Records – Access) project as its critical evidence base. MIRRA is a participatory research project, hosted at the Department of Information Studies at University College London (UCL) since 2017, which places Care Leavers as co-researchers at the heart of the work. The study has gathered evidence from care-experienced people, social workers, archivists, records managers, and researchers. The case context of care-experienced people provides a powerful focus for shifting views of records creation and ownership. Care-experienced people across the globe are situated within organizational systems that act as surrogate parents, but where the children or young people are often powerless to co-create and store their own memories, which would enable them to forge positive identities and revisit these through time. Positive and holistic life story narratives are rarely found. In addition, children’s care records are often accessible to care-experienced people only through legislative processes and without critical support. This research reframes the recordkeeping model, placing the care-experienced person at the heart of the process in order to ensure the co-creation of records and the maintenance of identity through time. The research acknowledges the complex and sometimes conflicting needs of diverse actors in children’s recordkeeping, including social workers, archivists, records managers, and researchers. It rethinks the actors’ relationships and responsibilities around the records and systems, drawing out a framework that makes explicit the value of active person-centred recordkeeping.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".