Educational development partnerships and practices: Helping librarians move beyond the one-shot
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
Given the current, widespread concern about “fake news” and information disorder, those working in post-secondary contexts have recognized a pressing need to develop students’ digital literacy (DL). Based on our experience collaboratively designing and delivering a faculty workshop on “Teaching Students about Fake News,” we see library connections to educational development as one way to address this need. Because faculty members design, develop, and deliver the requisite curriculum—and are often called upon to address the challenges that their students face in navigating, evaluating, and applying online content—they are frequently a first point of contact for help. Research examining student interactions with online news, social media, and other digital content also demonstrates how faculty play a vital part in facilitating and supporting critical digital engagement. All of this underscores the importance of faculty roles in promoting digital and information literacies. A fruitful strategy for librarians to build better connections with faculty is through educational development strategies.
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 | 0.001 | 0.001 |
| 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 | 0.003 | 0.009 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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