A History of ARLIS/NA MOQ = Un historique d'ARLIS/NA MOQ
Bibliographic record
Abstract
ARLIS/NA MOQ was founded in 1987 as the first Canadian chapter of ARLIS/NA (the Art Libraries Society of North America). The chapter is a non-profit, volunteer-run association of art librarians, archivists, curators, technicians, documentation specialists, and students in the regions of Montréal, Ottawa, and Québec City. Originally known variously as “ARLIS/MOQ,” “ARLIS M/O/Q,” or simply “M/O/Q,” the chapter officially changed its name to “ARLIS/NA MOQ” after 2006; although the more colloquial “MOQ” is often used by its members. The chapter’s founders recognized the benefits of coming together to build a professional community that straddles two provinces (Ontario and Québec), operates bilingually (in English and French), and comprises members associated with academic libraries, archives, museums, visual resource centres and other educational and cultural institutions. Drawing on archival sources from the ARLIS MOQ fonds and a close reading of the chapter’s publications, this history aims to document the origins and evolution of ARLIS/NA MOQ and draw attention to the association’s unique contributions to the field of art information specialists at the local, national, and international levels. This bilingual publication was produced as part of the author’s six-month sabbatical research carried out in 2024.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.010 | 0.009 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.036 | 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".