Bibliographic record
Abstract
Members of the Advisory Committee are enthused about the priority accorded intellectual freedom in the second draft of CLA’s proposed future plan. Under “Why we make a difference,” the very first reference is to “improving access to information for Canadians and working to protect intellectual freedom by advocating for the development of policies and position statements.” Within this broad framework, we think an important question for the CLA membership at large to consider is the scope and boundaries of the Association’s intellectual freedom policies, interests and advocacy. That is, does the membership support a “library focus” on library censorship issues? Or does the membership embrace a broader societal perspective grounded in Charter freedoms and responsibilities for all Canadians? There appear to be many nuances represented among CLA members. For example, some (if not all) school librarians see their role as promoting and teaching intellectual freedom in the context of citizenship responsibility. The CLA Award for the Advancement of Intellectual Freedom in Canada has several times been given to recognize contributions by individuals and groups beyond library borders. CLA itself is a member of the umbrella organization called the Book and Periodical Council, which among other initiatives sponsors Freedom to Read Week across Canada. When does a freedom of expression issue become a library issue? Can we comfortably snip off the library dimension of civil liberties? And if we do, are we open to the charge of being overly self-serving? It seems the media are often caught in the same self-serving boat – delighted to inflame library censorship controversies but holier-thanthou when their own press freedoms are under attack. In any event, are CLA members interested in broadening our civil liberties alliances and partnerships, or more comfortable with the more traditional library focus? There are many issues awaiting your perspective. Some are addressed by colleagues below – for example, the G20 Summit protests and the case for workplace speech. But there are so many others about which the Advisory Committee needs an understanding in order to be able to take action and make recommendations – for example, the WikiLeaks controversy, defamation suits and libel chill, transgender rights, campus clashes, saving indigenous languages, Internet neutrality, filtering, government criticism of works of art, film and television ratings, Canada Border Services censorship, decriminalization of prostitution, access to government information, hate speech and the human rights commissions, or any of the inevitable condemnations from time to time of authors, cartoonists, bloggers, journalists and political activists at home and around the world.
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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 | 0.021 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.014 | 0.027 |
| Scholarly communication | 0.043 | 0.048 |
| Open science | 0.004 | 0.015 |
| Research integrity | 0.022 | 0.020 |
| Insufficient payload (model declined to judge) | 0.088 | 0.030 |
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".