Bibliographic record
Abstract
At the University of Waterloo, librarians have been expanding their outreach to first-year students during orientation week dramatically over the past three years. Efforts have included involvement in department and faculty orientation events, as well as in a campus-wide orientation initiative called “Jumpstart Friday,” which aims to educate new students about the different services on campus that can help them to “jumpstart” their success. Librarians’ increasing participation in varied orientation events has necessitated that librarians streamline their outreach efforts for new students. Most recently, librarians have been designing their communication pieces and presentations with a focus on eliciting interest and positive first impressions about the library. To spark students’ interest in the library they aim to 1) create clear and concise messaging for delivering essential information, 2) demonstrate how the library will fit into students’ lives, and 3) deliver content in a high-energy and upbeat way. In this article, the authors outline the specific outreach approaches that librarians at Waterloo are currently taking in their communications and presentations to first-year students during orientation week.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.002 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.065 | 0.023 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".