Going social at Vancouver Public Library: what the virtual branch did next
Bibliographic record
Abstract
Purpose The purpose of this paper is to follow up on the 2009 publication “Building a virtual branch at Vancouver Public Library (VPL) using Web 2.0 tools” and to explore the work that VPL has been doing in the social media space over the past two years. Design/methodology/approach Following the launch of its new web site in 2008, Vancouver Public Library has continued to expand its online presence, both via its own web properties and in the social media space. At the core of the library's approach to web services is the desire to take the community development model online, and engage with communities in the spaces of their choosing. Findings The Web Team has been active in moving into the social media space, and was an early adopter of popular social networking sites such as Facebook and Twitter. The social bookmarking site Delicious also became an integral part of the new web site, being used as a management tool for the library's extensive collection of recommended web links. Since 2008 the Web Team has piloted a variety of other Web 2.0 and social media tools, pushing the library's online presence into new spaces while continuing to build on the successes experienced by its established accounts. Originality/value Libraries are very conscious of the need to leverage social media tools to engage with patrons, but are also facing the challenge of managing these tools with reduced staff and funding. VPL's success in this space offers a model of how to use these tools effectively to engage patrons, develop community, and maximize resources in a time of constrained budgets.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.043 | 0.014 |
| Scholarly communication | 0.029 | 0.009 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.026 | 0.006 |
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".