Bibliographic record
Abstract
Objective – To examine the evidence based management literature, as an example of evidence based practice, and determine how applicable evidence based management might be in the special library environment. Methods – Recent general management literature and the subject-focused literature of evidence based management were reviewed; likewise recent library/information science management literature and the subject-focused literature of evidence based librarianship were reviewed to identify relevant examples of the introduction and use of evidence based practice in organizations. Searches were conducted in major business/management databases, major library/information science databases, and relevant Web sites, blogs and wikis. Citation searches on key articles and follow-up searches on cited references were also conducted. Analysis of the retrieved literature was conducted to find similarities and/or differences between the management literature and the library/information science literature, especially as it related to special libraries. Results – The barriers to introducing evidence based management into most organizations were found to apply to many special libraries and are similar to issues involved with evidence based practice in librarianship in general. Despite these barriers, a set of resources to assist special librarians in accessing research-based information to help them use principles of evidence based management is identified. Conclusion – While most special librarians are faced with a number of barriers to using evidence based management, resources do exist to help overcome these obstacles.
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 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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.214 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 teacher head, 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".