Manitoba Public Libraries Response to the Early Stages of COVID-19
Bibliographic record
Abstract
Like many libraries across Canada, Manitoba public libraries have grappled with the challenges that COVID-19 has presented. Libraries have struggled to remain operational and offer a high level of service to patrons within the constraint of public health orders, all the while ensuring the safety and employment of their staff. Within the ever-changing environment of COVID-19, the Manitoba Library Association recognized the need to gather information from the library community in order to better position themselves to lend support and in an attempt to bridge information gaps. This article describes a study conducted by the Manitoba Library Association whereby fifty-five Manitoba public libraries were surveyed to identify how they were responding to COVID-19 and what their needs might be. The survey questions were divided into 6 sections (facilities, services, communications, staffing, connecting, wrap-up) and the results provide information and insight into how the Manitoba library community has dealt with the pandemic. More importantly, the results can serve to guide other libraries in decision-making and preparation for a pandemic.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.027 | 0.005 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 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".