Bibliographic record
Abstract
Support for Open Access (OA) as an accepted model for scholarly publishing is changing the academic landscape for today's graduate students.The Open Access movement has the potential to impact many facets of the graduate experience.This may include participation in peer-reviewed publishing initiatives, learning to become members of the community of researchers and producers of scholarly works, and finally, involvement in the Open Education Resource (OER) movement.Graduate student participation in student peer-reviewed journals is increasing as tomorrow's scholars seek both the experience of the publishing process first hand, as well as the opportunity to get a professional "foot in the door".Current OA journals using efficient Open Journal System (OJS) tools and work flows provide a low-cost, inclusive point of access and play an important role in introducing the critical peer review process to future faculty and researchers.When we are educating graduate students, acquiring confidence in the practice of scholarly research, writing and review is as important as the discipline-specific expertise.Many of our students may find OA publishing of their thesis to be an important step in their induction into the academy.At the University of Toronto the eThesis initiative requires that all graduate students contribute their thesis or dissertation to the institutional repository where it may be immediately accessed to scholars in their field and prioritized by primary scholarly search engines.The policy and practice related to OA publishing observed within the university environment will inform their understanding of cultural norms.This eThesis program provides an early exposure to Open Access publishing practice.Finally, as global citizens, our students value the opportunity to share their work beyond the borders of the relatively wealthy western world institutions of higher education, and also to access resources beyond the subscription limitations of their own place of study.New patterns of practice rooted in a new culture of social networking are emerging for the graduate student community.
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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 | 0.009 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.023 | 0.019 |
| Open science | 0.004 | 0.034 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.437 | 0.233 |
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".