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
Purpose The purpose of this paper seeks to provide an in-depth overview of a series of fake news information literacy library workshops, which were offered 19 times over the course of 2 years. It examines the results of a fake news game, which was played with a wide variety of audiences. Design/methodology/approach This case study examines workshops offered by two librarians at [name of institution], a major research institution in [city], [country]. It describes the workshops in detail and demonstrates how others may adopt this model. Findings The authors found that while high school students proved to be the most adept at recognizing fake news, the literature suggests that mere exposure to digital media is not sufficient in preparing Generation Z in their digital literacy critical assessment skills. Practical implications Library and information professionals are provided with the tools to adapt this workshop to suit the needs of their respective users. Originality/value This paper examines how a workshop can be adapted to seven unique audiences, spanning from high school students to university alumni. It incorporates the Association of College and Research Libraries framework and the latest literature into informing its practice.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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