The Medical Library Association's Master Guide to Authoritative Information Resources in the Health Sciences
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
Just When We Thought Things Were Running Smoothly…'' The last chapter deals with how the financial disaster of 2008 changed issues in the workplace for people.Chapters five, six, and eight are subdivided.''Chapter Five: Systems Thinking Simplified-Four Primary Concepts'' includes the seven levels of living systems, the twelve natural laws of living systems, the A-B-C-D-E systems thinking approach, and the rollercoaster of change.These concepts continue throughout the rest of the book.''Chapter Six: Developing Your People Plan-A Systems Thinking Approach'' details ten steps and a parallel process.''Chapter Eight: Ten Critical HR Issues within Libraries'' is highly relevant and valuable in itself.Other features include a list of figures, a bibliography of resources mentioned in chapter notes, and an index that includes some cross-referencing.The black-and-white figures are useful in understanding the presented concepts.Because the authors are Australian and Canadian, some of the content will differ for Americans.For example, the generational profiles provided come from Canadian analysis and do vary from American populations in some ways.Overall, the issues addressed in the work are universally relevant to academic libraries and can be generalized to health sciences libraries.
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 | 0.011 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.006 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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