Bibliographic record
Abstract
Clearly archives are not neutral: they embody the power inherent in accumulation, collection, and hoarding. (Sekula, 2003: 446) Introduction The ‘Finding Myself in the Archives’ (2017) project undertaken by the Ward Museum in Canada is illustrative of creative approaches to opening up the ‘Archive’ to new forms of scrutiny and new interpretive voices. It does so in a way that allows for collective reorientations of history, culture and witness through innovative curatorial practice. Students who had taken part in the project were asked to research and find the ‘stories’ connoted by 54 objects from the collection of the University of Toronto. They were to relate the objects and associated stories not just to their own lives but also to the lives of the marginalised communities those objects touched. While the participants were students studying on a museum programme, they were a ‘community’ in their own right, a professional community in the making, one that would shortly form part of a new generation of archival professionals, guardians of knowledge and potential gatekeepers. This and many other recent projects, such as those undertaken as part of the Research Councils UK Connected Communities programme and Digital Transformations theme, point to a sea-change in institutional and community relationships that increasingly foregrounds collaborative approaches (Facer and Enright, 2016). Such approaches increasingly invite the community into the institutional archival space and legitimise the non-institutional archive, recognising the reciprocal value and authority of the community and the vibrant potential of collaborative dialogues that challenge traditions, innovate new practices and share the inherent power of the archive in all its emergent forms (Crooke, 2007; Flinn, 2010; Hacker, 2013). The archive as community The archival space is one populated by communities of all sorts: those represented, those who curate and care for its contents, those who excavate and interpret, and those curious about what, if anything, it has to say about their own lives and histories. These roles, often separated and oppositional in the past, are increasingly disrupted and interrogated by a combination of new approaches, materialities, digital technologies and the pressures of the prevailing economic climate. The potential to collect, connect and challenge knowledge, remix materials, share responsibilities and flip boundaries is palpable and ongoing (Smith, 2007).
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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.026 | 0.112 |
| Scholarly communication | 0.020 | 0.018 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.004 | 0.005 |
| 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".