Publishing (and Forgetting) the Small or Medium-sized Scholarly Edition or Cultural Heritage Collection as Linked Open Data: Using Zenodo and Github to Publish the Visionary Cross Project (Abstract)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We discuss an approach to publishing heterogeneous file data and long-form humanities research as both linked open data and a (human readable) digital scholarly edition using Zenodo and Github. This approach is broadly generalisable and answers a number of long-standing issues surrounding the publication of data and results in DH: 1 It promotes the discovery and long-term survival of published data and results with no requirement for future maintenance; 2 It conforms to archival standards and principles; 3 It is fully available for future extension, addition, excerption, reuse, repurposing, or reanalysis by others without negotiation; 4 It ensures that data and contextual analysis are linked bi-directionally meaning that users are always able both to access the discrete data points from which a Humanities-focused analysis and commentary is build and understand each data point in the context of these larger synthetic research products.
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.
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Scholarly communicationOpen science Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | Scholarly communicationOpen science Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Not applicable | medium |
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.007 | 0.000 |
| Scholarly communication | 0.084 | 0.062 |
| Open science | 0.007 | 0.012 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it