Demonstrating the financial impact of clinical libraries: a systematic review
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
OBJECTIVE: The purpose of this review is to evaluate the tools used to measure the financial value of libraries in a clinical setting. METHODS: Searches were carried out on ten databases for the years 2003-2013, with a final search before completion to identify any recent papers. RESULTS: Eleven papers met the final inclusion criteria. There was no evidence of a single 'best practice', and many metrics used to measure financial impact of clinical libraries were developed on an ad hoc basis locally. The most common measures of financial impact were value of time saved, value of resource collection against cost of alternative sources, cost avoidance and revenue generated through assistance on grant submissions. Few papers provided an insight into the longer term impact on the library service resulting from submitting return on investment (ROI) or other financial impact statements. CONCLUSIONS: There are limited examples of metrics which clinical libraries can use to measure explicit financial impact. The methods highlighted in this literature review are generally implicit in the measures used and lack robustness. There is a need for future research to develop standardised, validated tools that clinical libraries can use to demonstrate their financial impact.
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 | 0.023 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.005 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it