Protecting Dispersed Collections: A Framework for Managing the at-Risk Heritage Assets of Catholic Religious Institutes
Bibliographic record
Abstract
The aim of this project was to gather information on the archive management practices for all religious institutes of England and Wales and to propose viable solutions for their long-term preservation, ensuring their continuity beyond the lifespan of each institute.As a result of the decline in vocations, many religious institutes are disbanding with the resulting existential threat to their significant archive collections. These collections are not only important to the religious institutes themselves, allowing their charism and identity to remain in perpetuity, but are also invaluable to historians of education, medicine, migration and exile, and other topics now considered secular.Solutions that have been attempted in the UK have been limited in scope, although there are examples of centralised repositories in Europe, the United States and Canada specialising in storing the archives of religious institutes. Of particular importance in this context are the Heritage Centre for Monastic Life in St. Agatha, Nijmegen, and the KADOC Documentation and Research Centre on Religion, Culture and Society in Leuven, whose repositories were visited as part of this project. There have also been attempts in the UK, Ireland and elsewhere to collect information on collection management practices in the form of surveys and inspections.Building upon this research, a survey was sent to all religious institutes in England and Wales to collect information on their collection management practices and future plans for the storage of their archive.As a result of this survey, the main findings and recommendations include: the need to convene a ‘Repository Working Group’ involving representatives from religious institutes, Catholic stakeholders, and archives associations to discuss the feasibility of establishing repositories, including commissioning a comprehensive feasibility study and cost analysis to determine viability; collaboration with international groups facing similar challenges; raising awareness about archive preservation amongst religious institutes; encouraging basic listings of collections; providing archival training opportunities, and advocating for funding and access to archives.The report also stresses that religious institutes are not alone in facing the challenges of at-risk and dispersed records. Indeed, the recommendations of this report will be relevant to many institutions and organisations storing archives and so have broader implications for the archives sector as a whole.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| 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".