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
Since the inception of indexed-based web-scale discovery services for libraries, JSTOR has been providing metadata to Primo (Ex Libris), EDS (EBSCO), Summon (Serials Solutions), and WorldCat Local (OCLC). By participating in these services, JSTOR’s aim was to help libraries leverage their significant investments in their discovery service of choice and to help students, faculty, and researchers find the content available on the JSTOR platform at their chosen starting point. While there have been a number of studies on these discovery services, there is little written about the impact on content usage from the perspective of the content provider. JSTOR has undertaken a comprehensive analysis of the use of their content in the discovery services to better comprehend “how” usage (as measured by COUNTER) is being impacted at institutions that have implemented these services, investigate “why” these usage changes might be occurring, and to gain an understanding of “what” content providers, libraries, and the discovery software providers can do to make this a more virtuous circle.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.001 | 0.000 |
| 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