Bibliographic record
Abstract
Undeniably, working in an environment that challenges the status quo is not without its problems. Members of the service redesign teams who participated in the West Ottawa Valley Network experience confess that many times during the process they felt a threat to their own job security along with uncertainty about their future roles and responsibilities. June Merkley points out that "working outside one's "normal comfort level" in a non-traditional leadership role has it's own set of difficulties, and dealing with multiple network members adds a dimension of complexity not encountered at the single site level." But she believes that "the challenges encountered within the network are helping to broaden the scope of job knowledge and communication skills. This can only have a direct and positive impact on the day-to-day tasks, while providing value to both the employee and employer". As a career management strategy, healthcare managers should seek out opportunities beyond their normal range of accountability, participate in activities that encourage the growth of new skills or hone skills that are a bit rusty. Often these projects will cause some anxiety or discomfort but the rewards, both short and long term, far outweigh the short-term pain.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.018 | 0.013 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".