Advocacy and Collaboration in a Time of Global Upheaval: Insights from IFLA Regional Divisions
Bibliographic record
Abstract
At the 2025 IFLA World Library and Information Congress (WLIC) in Astana, the IFLA Regional Council brought together librarians and advocates from across the globe to reflect on the pressing challenges facing libraries in an era of political polarization, social unrest, and digital transformation. Under the theme "Advocacy and Collaboration in a Time of Global Upheaval: A Unified Response from the IFLA Regional Divisions," the session highlighted how libraries are navigating censorship pressures, promoting multicultural engagement, championing access to information in overlooked communities, and responding to emerging threats to democratic participation. The presentations spanned continents and contexts, from European courts to Canadian prisons, from African misinformation campaigns to Latin American policy initiatives, demonstrating that while challenges vary by region, the library profession's commitment to intellectual freedom, equity, and democratic values remains universal. The full recording of the session is available on the IFLA YouTube channel.
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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 | 0.040 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.061 | 0.032 |
| Scholarly communication | 0.042 | 0.022 |
| Open science | 0.004 | 0.038 |
| Research integrity | 0.011 | 0.017 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".