Measuring the Effectiveness of Queen Elizabeth II Library Document Delivery Operations Before and After the Implementation of Relais International’s Enterprise Document Delivery Software
Bibliographic record
Abstract
Objective - To compare the performance of the Queen Elizabeth II Document Delivery operation before and after the implementation of Relais International’s Enterprise document delivery software. Methods - This paper employs methodology established in the Association of Research Libraries’ 1998 publication, “Measuring the Performance of Interlibrary Loan Operations” and repeated in ARL’s “Assessing ILL/DD Services: New Cost- Effective Alternatives,” published in 2004. In both studies, three measures were used to evaluate the efficiency of document delivery operations: fill rate, turnaround time and direct costs. Both studies offer ARL benchmark or mean scores for each efficiency measure. This paper compares Queen Elizabeth II Document Delivery (QEII/DD) scores for each efficiency measure with those reported in both ARL studies. Results - Data for the two periods under review, 1999-2000 and 2004-2005, indicate that Borrowing fill rates remained relatively stable, showing only a 3% drop in the latter year, while lending fill rates showed a significant increase (11%). Turnaround times for filled QEII/DD borrowing returnable requests were faster on average by 4.2 days or 24%. Turnaround times for QEII/DD non-returnable borrowing requests also show improvement: a filled non-returnable request was faster on average by 1 day or 12%. The average cost of a QEII/DD borrowing request has remained stable: $22.82 in 1999-2000 and $22.61 in 2004-2005. In contrast, the average cost of a QEII/DD lending request has increased slightly: from $11.08 in 1999-2000 to $13.12 in 2004-2005. Conclusion - Both the implementation of Relais document delivery software and the delivery of returnables (loans) by courier between consortium members have allowed the QEII/DD unit to post modest gains in both fill rates and per unit costs and more substantive gains in turnaround time.
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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 | 0.021 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".