Describing the HSS Commons: The View from Metadata
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
In the first year since the launch of the HSS Commons, members have added over 100 publications and the features of the repository’s design are beginning to manifest. Building from Kim Martin’s talk on the possibilities for serendipity in browsing the Commons (Martin, 2022), I explore the descriptive metadata for this first cohort of publications, with particular focus on author-supplied keywords. Information studies predicts that author-supplied metadata enacts diverse sense of the intent and operation of fields, a tendency toward very high-level or general terminology, and the relevance of interaction design choices. This paper presents the metadata practices already visible in the HSS Commons and suggests interaction and maintenance design that can facilitate serendipitous discovery without compromising on the usability and creativity of the platform.
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.
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 | 0.011 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.026 | 0.053 |
| Open science | 0.019 | 0.016 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it