An Open Social Scholarship Path for the Humanities
Bibliographic record
Abstract
Open digital scholarship is significant for facilitating public access to and engagement with research, and as a foundation for growing digital scholarly infrastructure around the world today and in the future. But the path to adopting open, digital scholarship on a national—never mind international—scale is challenged by several real, pragmatic issues. In this article, we consider these issues as well as proactive strategies for the realization of robust, inclusive, publicly engaged, open scholarship in digital form. We draw on the INKE Partnership’s central goal of fostering open social scholarship (academic practice that enables the creation, dissemination, and engagement of open research by specialists and non-specialists in accessible and significant ways). In doing so, we look to pursue more open, and more social, scholarly activities through knowledge mobilization, community training, public engagement, and policy recommendations in order to understand and address challenges facing digital scholarly communication. We then provide tangible details, outlining how the INKE Partnership puts open social scholarship theory into practice, with an eye to a more open and engaged future.
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 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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".