SLIS Student Research Journal, Vol.7, Iss.1
Bibliographic record
Abstract
This issue of the SLIS Student Research Journal features two articles addressing schema, structure, and theory in LIS.In an invited contribution, Dr. Mary Bolin proposes applying linguistic theories and frameworks to LIS research.Bolin states that librarians "already recognize the significance of the language that we use" (p.1), and suggests that interdisciplinary methods may strengthen investigations in areas of LIS research concerned with semantic structures and communicative events.Bolin suggests numerous convergences between the disciplines: how typology may be used for parsing qualitative data, or semantic frames for examining relationships and meaning in metadata schemas; discourse analysis and genre theory also offer intriguing possibilities for examining user communities in library contexts.In our peer-reviewed section, MLIS candidate Chloe Noland evaluates the interoperability of Library of Congress Classification and Elazar at two libraries of the American Jewish University.Noland compares bibliographic metadata from the two collections, considering semantic accuracy and user impacts.Noland determines that although in the academic context it is unclear which classification system may be preferable, "for purposes of Jewish themes and subjectsElazar overwhelmingly provides the best specificity" (p.12).This article will be of interest to special collections librarians and cataloguing and metadata specialists.This thirteenth issue of the SRJ closes my tenure as Editor-in-Chief with the journal.It has been a year of significant development in organizational planning, yielding a refreshed strategic plan for the SRJ, revisions to our recruitment, orientation, and training for editors, and the launch of a new peer-reviewed reviews section for the journal.
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 | 0.046 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.001 |
| Scholarly communication | 0.015 | 0.076 |
| Open science | 0.005 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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; both teacher heads agree on what is shown here.
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".