Bibliographic record
Abstract
BackgroundIn late 2015, an Open Access Advisory Committee was struck as a sub-committee of Senate Library Committee and charged with drafting a university-wide Open Access (OA) Policy.The OA Policy's goal was to "provide consistency with the Tri-Agency Open Access Policy, to maximize the exposure of the outputs of SFU scholarship, and to work toward a sustainable alternative to current challenges in the scholarly publishing market" (Bird, 2016, para.1).After extensive consultations and meetings with various campus groups and departments, Senate endorsed the SFU OA Policy in January 2017.The SFU Open Access Policy acknowledges the commitment of faculty, students, and postdoctoral fellows to share the products of their research with the broadest possible audience, including other scholars, practitioners, policymakers, and the public at large.The OA Policy commits SFU researchers to deposit their authored and co-authored scholarly articles in Summit, SFU's institutional research repository, granting
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.
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 | 0.015 | 0.042 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.025 | 0.009 |
| Insufficient payload (model declined to judge) | 0.280 | 0.188 |
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".