The Role of Multidimensional Library Neutrality in Advancing Social Justice: Adapting Theoretical Foundations from Political Science and Urban Planning
Bibliographic record
Abstract
There is an ongoing, polarizing debate in the library profession and scholarship regarding the perceived incompatibility between library neutrality (embedded in the profession through the American Library Association’s Library Bill of Rights), and social justice goals. This article asserts that the growing antipathy on the part of some library practitioners and scholars towards neutrality and intellectual freedom is owed at least in part to the profession and scholarship having never articulated an adequate definition of what is meant by neutrality. As a result, the profession lacks a theoretical framework situating the library and library staff as political actors within a multicultural and largely urban society. We argue that such a framework may be drawn from the literatures of political science and urban planning. By positioning libraries and library workers within the context of liberal-democratic institutions – as is the case for urban planners in their theoretical literature – LIS theory can find more durable foundations for its core values. Stressing planning’s commitments to the participation of multiple publics, to dialogue, mediation and to consensus-building through liberal institutions, we develop a multidimensional understanding of neutrality premised on values, stakeholders, processes and goals which we then apply to these planning modes. Finally, we propose a model of “Communicative Librarianship” as best exemplifying these four dimensions of neutrality and their attendant democratic commitments.
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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 | 0.023 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.010 | 0.111 |
| Scholarly communication | 0.019 | 0.013 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".