Reflections in the Fishbowl: the Changing Role of Law Librarians in the Mix of an Evolving Legal Profession
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
This paper by Victoria Elizabeth Baranow is a reflective piece after co-moderating a session at the 2017 CALL Conference in Ottawa with Shaunna Mireau. The session was titled ‘Unconference Through the Fishbowl: The Changing Role of Law Librarians in the Mix of an Evolving Legal Profession.’ A play-by-play article on the session was written based on notes and recollections from the session and published in the TALL Quarterly, the journal by the Toronto Association of Law Libraries. 1 The article was used as the basis for this paper; which goes one step further in attempting to answer some of the big questions we are faced with each day while also questioning some of the assumptions and wider cultural forces at play in our law librarianship profession. **
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 | 0.003 | 0.000 |
| 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 | 0.000 | 0.006 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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