The Creation of the CFLA/FCAB Truth and Reconciliation Committee: The First Report
Bibliographic record
Abstract
One of the top priorities of the newly formed Canadian Federation of Libraries Associations/Fédération canadienne des associations de bibliothèques (CFLA/FCAB) was to create a Truth and Reconciliation Committee to promote initiatives in all types of libraries to advance reconciliation by supporting the Truth and Reconciliation Commission of Canada’s Calls to Action, and to support collaboration in these issues across the Canadian library communities. Thus, this first committee was formed with representatives of the CFLA/FCAB Board and library association’s nominees from all across Canada. From the beginning, the Committee worked with Indigenous leaders and sought the guidance of Indigenous Elders. This paper presents a summary of this Committee creation, organization, and work, as well as the recommendations to the CFLA/FCAB Board. L’une des principales priorités de la Fédération canadienne des associations de bibliothèques (FCAB), qui a été récemment mise sur pied, est la création d’une comité de vérité et de réconciliation afin de promouvoir des initiatives dans tous les milieux de bibliothèque pour faire avancer la réconciliation en appuyant les appels à l’action de la Commission de vérité et de réconciliation du Canada et en appuyant la collaboration concernant ces enjeux parmi la communauté des bibliothèques au Canada. Alors, le premier comité a été formé avec des représentants du conseil d’administration de la FCAB et des associations des bibliothèques à travers le Canada. Dès le début, le comité travaille avec des leaders autochtones et recherche les conseils des ainés autochtones. Cet article présente un sommaire de la création, de l’organisation et du travail du comité ainsi que des recommandations au conseil de la FCAB.
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 | 0.085 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.022 | 0.005 |
| Scholarly communication | 0.028 | 0.007 |
| Open science | 0.007 | 0.010 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.009 | 0.005 |
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".