Usage Data of an OpenAccess e-Journal in a Digital Repository.
Bibliographic record
Abstract
Of fifty-eight library and information science programs currently accredited by the American Library Association (ALA) in the United States and Canada, the University of Southern Mississippi’s School of Library and Information Science (SLIS) is one of only twenty offered completely online and is the only ALA-accredited program in the state. Part of the accreditation process includes maintaining contact and communication with students and alumni. This can be a difficult task to accomplish when faculty may never meet students in person and students are located all over the state, the United States, and the world. One idea to meet this accreditation requirement was to create an online newsletter; students and alumni would send in updates and would receive program updates. Fortunately, reaccreditation coincided with the university library’s introduction of The Aquila Digital Community (http://aquila.usm.edu/) hosted through Digital Commons. Once Aquila was in place and it became obvious that Digital Commons made it easy to do much more than newsletters, the focus moved to an open access journal called SLIS Connecting (Image 1). The new purpose became “to share news, information and research with future students, current students, alumni, faculty, and the general population through selected faculty publications, invited student publications, refereed publications, and through regular columns.”[1] The first issue was electronically published in February 2012 and the second in October 2012. The third issue was published in February 2013 and contains the first paper submitted from an author not affiliated with SLIS. SLIS Connecting, an electronic open-access journal hosted in a university depository, is currently indexed in Google Search and in Google Scholar.
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 | 0.004 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.025 | 0.035 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.058 | 0.071 |
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".