BCLA Literacy Interest Group Annual Report for 2009-2010
Bibliographic record
Abstract
• IG members continue to sit on Literacy BC’s ELMO Reviews Working Committee [ELMO=Exemplary Literacy Materials Online]: https://www.elmoreviews.ca/ • IG members sit on the Advisory Board for the West Coast Reader: http://blogs.capilanou.ca/westcoastreader/ • IG members are part of the advisory group for ABC Life Literacy Canada’s Good Reads programme and are actively involved in this national programme’s rollout. See: http://abclifeliteracy.ca/en/good-reads • IG members are part of the advisory group working with the Canadian Commission for UNESCO to develop the International Adult Learner Week programme in Canada. See: http://www.unesco.ca/en/activity/education/Adu ltLearners.aspx We continue to regularly share literacy information within our IG and with the BCLA membership at large; we also serve as a resource on literacy matters to the BCLA Executive. We know that national organizations and NGOs are impressed with BC’s libraries and their commitment to literacy. For example, the Canadian Commission for UNESCO is very pleased with the response it gets from BC libraries for International Adult Learner Week. We also know that libraries all over BC are committing themselves to the Community Literacy Planning Process facilitated by the 2010 Legacies Now Programme. Not only are libraries at the planning table but, they’re also important partners in the implementation of Community Literacy Plans. See: http://www.2010legaciesnow.com/literacy_now_commu nities/
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.251 | 0.224 |
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".