A Position of Strength: The Value of Evidence and Change Management in Master Plan Development
Bibliographic record
Abstract
Libraries are experiencing significant change in how space is being used as well as increasing pressure from their funding and governance bodies to demonstrate the continued need for library physical space. There is a growing demand for library spaces that reflect different ways of accessing and using information, support learning and building community, and encourage creativity and the creation of new knowledge. To assist them in determining how to move forward, many libraries are developing master plans – multi-year high-level plans providing direction and vision but allowing flexibility to accommodate unanticipated needs – for their physical spaces and service delivery models. The challenge for libraries is to ensure that their master plans reflect the dynamic world in which they are situated and are supported by clients and other library stakeholders.
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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 | 0.639 | 0.798 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.027 | 0.011 |
| Science and technology studies | 0.010 | 0.056 |
| Scholarly communication | 0.052 | 0.086 |
| Open science | 0.013 | 0.034 |
| Research integrity | 0.027 | 0.032 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".