Enhancing collaboration and dissemination through a faculty scheduled development management framework
Bibliographic record
Abstract
Colleges provide professional development opportunities to faculty to promote knowledge growth and improvement of skills. At Camosun College, Scheduled Development (SD) time for faculty is based on the educational practice and recognition of the need for continuous professional development of faculty members. The paper presents the development of an online environment to enhance and promote active collaboration among faculty in the context of professional development. The Scheduled Development (SD) Connect tool is under development, implementation and is currently undergoing testing. SDConnect® is a multi-facet targeted software tool that aids in dissemination, tracking, integration, and collaboration, of faculty SD for post secondary institutions. The tool will also enable Camosun College faculty and staff to access the information database on SD activities, with the goal that it may lead to active collaborations and synergies among the faculty, departments and schools. This project will also enable the administration to efficiently administer SD proposals and approvals and to establish historical records and trends of the SD activities of faculty for better resource management. SDConnect® is part of an ongoing project called DEAL (Diversity In an Environment of Accessible Learning) at Camosun College.
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 | 0.041 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".