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
In recent years, digital outreach efforts, including social media campaigns, have been explored by archival institutions in an effort to engage with online audiences. It is, however, difficult to know what makes effective social media outreach. This article considers literature from the field on the topic of digital archival outreach and archival outreach in general, and measures user engagement through ‘likes,’ ‘saves,’ follows, and comments, to explore the possibilities of social media promotion for archival institutions by analyzing the Tiktok activity of the Special Collections and Archives department at Liverpool John Moores University (LJMU SCA). Although extensive research would need to be done in order to determine the concrete, real-life impact of these efforts, it is clear that through their regular, varied posts, and efforts to appeal to existing fan groups online, LJMU SCA’s social media campaign is successful in connecting directly with a large number of people, and drawing attention to their activities and collections, as well as archival work in general.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.005 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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