The Manitoba Association of Health Information Providers (MAHIP)
Bibliographic record
Abstract
CHAPTER HIGHLIGHTS / FAITS SAILLANTS DES CHAPITRES The Manitoba Association of Health Information Providers (MAHIP)The Manitoba Association of Health Information Providers (MAHIP) was very active in 2012Á2013.Three journal clubs were held in 2012Á2013.A critical appraisal checklist was utilized to assist in appraising articles and guiding discussion (Glynn L. A critical appraisal tool for library and information research.Library Hi Tech.2006; 24(3): 387Á399).In 2013Á2014 we will continue to evaluate the process of journal club facilitation, implement an evaluation form, and review additional journal club facilitation guidelines.Since 2010, library associations in Manitoba have been assessing the current structure of library associations and determining support for the creation of an umbrella library organization.MAHIP held a members meeting on 19 September 2012 to discuss MAHIP's potential involvement in such an association.MAHIP's President and Vice-President attended three meetings of the Manitoba Library Associations Working Group.A sub-committee of the Working Group was created to draft an organizational structure reflecting the needs of all participating associations.Results from the sub-committee are still pending.In 2012, Ada Ducas, Kerry Macdonald, and Lisa Demczuk received CHLA/ABSC's Chapter Initiatives Grant for their research on ''Benchmarking Canadian Health Facility Libraries''.
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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.056 | 0.010 |
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".