From Coexistence to Convergence: Studying Partnerships and Collaboration among Libraries, Archives and Museums
Bibliographic record
Abstract
Introduction. The convergence of libraries, archives and museums is an evolving phenomenon that has garnered increased attention in the literature and professional practice over the past decade. To date, little research exists documenting the experiences of these institutions as they engage in different forms of collaboration and convergence. Method. Using a series of on-site, semi-structured interviews of professionals conducted in 2010 and 2011, the study examined initiatives involving different forms of collaboration and convergence, and different stages of the process in two institutions in Canada and three in New Zealand. Analysis. The interviews were audio recorded and a descriptive summary of each interview was prepared. We examined the summaries and identified themes within and across the institutions. Results. Findings suggest the motivations that led to the various projects reflected the discourse, beliefs, and values of the professions at the time the projects took place, and occasionally, administrative expediency. Aspects that emerged from the interviews correlate broadly to six themes: to serve users better; to support scholarly activity; to take advantage of technological developments; to take into account the need for
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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 | 0.019 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.018 | 0.018 |
| Scholarly communication | 0.016 | 0.017 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.002 | 0.003 |
| 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".