Taking it to the Streets: using an open policy environment and outreach to help shape Canada’s national collection
Bibliographic record
Abstract
In its role as a national library and archives, Library and Archives Canada develops its published collection systematically through Legal Deposit. As a blunt instrument, legal deposit is intended to assure that the published heritage of a nation is acquired and made accessible to current and future generations of clients. However, LAC has become more and more selective in what it acquires on legal deposit, while also understanding that not all the publishers and music producers from whom it would like to acquire material participate in the program. As part of the renewal of its legal deposit program, it has been drafting a new collection development policy for publications, employing traditional consultation with members of its external stakeholder committees - including librarians - as well as an open information environment that leverages new technology to invite a wider audience to participate directly in the policy-making process. Using such open dialogue to build policy is one way in which LAC supports Canada’s objectives on Open Government. While it may be primarily the users of the collection who are most interested in influencing the collection policy, LAC recognizes that the success of the LD program is also intimately connected to another group of stakeholders who use its services: Canadian publishers. Like other national libraries, LAC offers a suite of services to Canadian publishers, including ISBN, ISMN, ISSN issuance, cataloguing-in-publication and legal deposit, and relies upon publishers to help it assemble a valuable and comprehensive record of Canada’s published heritage. To that end, LAC has developed a Publisher Outreach Strategy (POS) in parallel with the collection development policy, with the overarching aim of improving publisher participation in legal deposit. The pillars of the strategy involve rethinking LAC’s approach to business intelligence gathering and dissemination; increasing awareness and use of LAC’s services to publishers; and developing staff capacity to effectively implement the new approach. This paper explores the ways in which LAC is implementing these new ways of doing business to support development of the national collection of publications, the reaction internally and externally to this approach, the advantages and challenges, and the results to date.
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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 | 0.033 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.068 | 0.034 |
| Scholarly communication | 0.043 | 0.015 |
| Open science | 0.005 | 0.020 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.011 | 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".