Development of a Tool to Evaluate Staff Requests for Funding Support to Attend Conferences
Bibliographic record
Abstract
INTRODUCTION External conferences continue to play an integral part in most educational programs for pharmacy staff. Although they are not the only component of such programs, the value of networking, sharing of ideas, and stimulation obtained through attendence at conferences should not be underestimated. However, with decreases in travel budgets — if they exist at all — the absence of travel assistance in most written contracts, and the decreasing availability of travel grants, there is a need to look at funding policies for attending external conferences. 1 Amalgamation into one provincial pharmacy program within the Alberta Cancer Board provided the opportunity for us to compare the existing internal policies of the pharmacy departments of the Tom Baker Cancer Centre and the Cross Cancer Institute and to develop a single consensus framework. The issue of external conference funding was discussed by a team consisting of 5 members from our pharmacy department, representing administration, specialty practice, general practice, pharmacist and technician perspectives. The objective was to formulate one process for a provincial department of pharmacy. The approach of the development team was to ascertain the organizational rules that pertained and to benchmark other colleagues’ practices, since the medical literature on this topic is sparse.1 The final result of this work is shared in this paper.
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 | 0.036 | 0.095 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.016 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".