Managerial learning: changing times for medical laboratory managers: a personal experience
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Sue Vollbrecht worked as a laboratory technician for many years before being promoted to her present position as laboratory manager. She was promoted because of her interest in change management and her desire to have an impact on the future of her organization. This interview has as its foundation a school paper that she wrote as a means of assessing her managerial learning. The interview provides insight into the vast amount of change in the medical laboratory world, and some of the learning experiences that have been instrumental in helping her to develop the skills necessary to manage and successfully work with change. Using key events as pivotal points for reflection, she deduces the basic theories that she considers necessary for successful change management, and then considers them in the light of some of the management literature in the field. Major themes discussed are career development for people interested in working with organizational change, learning at work using an action learning approach, trust building through communication, and working with stakeholders effectively to bring about change.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it