Third Place Libraries as a Space for Intercultural Participation: A Dynamic Learning Model for Creating Culturally Safe Environments
Bibliographic record
Abstract
One of the main sources for re-conceptualizing the model of libraries, especially public libraries, as third places remains Robert Putnam in Better Together (2005) based on his work in Chicago Public Libraries, which he described as the "New Third Places". But what was new here when Putnam spoke of these "New Third Places"? He was then referring to the new context of diversity, and even super-diversity (Vertovec 2007), characteristic of our current societies. According to Putnam, the library as this "New Third Place" appears as a response to this problem of social distance and unease because it has this capacity to produce social capital, to shape networks based on meaningful interactions and trust (Putnam 2007). This question of "meaningful interactions" - which may bring us to a shared identity - leads us to be concerned with precisely what may constitute obstacles to relationships, communication and participation. How can libraries create capacities to facilitate meaningful interactions across various lines of difference in increasingly diverse public spaces ? (as Aabo and als. asked as well). Now, this issue of "meaningful interactions" is also a basic tenet of intercultural theory and practice and, as such, we believe it should be taken into account in the analysis of social dynamics within libraries. The intercultural approach refers to a dynamic model of learning, derived from anthropology, for professionals and staff who are confronted with intercultural situations. In this regard, we propose to develop an intercultural approach model that can be operationalized in libraries through reflective practice (White and Martel, 2020). This model is also extended to interrogate and develop in a critical and anti-racist perspective, the way in which our services, our programs, our spaces, our collections can be identified as racialized, racist, oppressive, colonizing (Matthews 2020). We will then consider how, depending on the type of conversation (and depending on the goals of intercultural bridging and/or our commitments related to equity-diversity-inclusion-anti-racism), we can rethink libraries as Third Places through a continuum of places for intercultural and critical reflexivity. We will conclude by exploring avenues for practice and research related to these new issues of "conversational literacy" (Lankes 2011, 73) within the profession, within organizations, within our communities. Aabø, S., Audunson, R., & Vårheim, A. (2010). How do public libraries function as meeting places? Library & Information Science Research, 32(1), 16‑26. Lankes, R. David. (2011). The Atlas of New Librarianship. The MIT Press. Matthews, A. (2020). Racialized Youth in the Public Library: Systemic Racism Through a Critical Theory Lens . Partnership: The Canadian Journal of Library and Information Practice and Research, 15(1). Putnam, Robert D, Lewis M Feldstein, et Don Cohen. (2005). Better Together: Restoring the American Community. London: Simon & Schuster. Putnam. Robert R. (2007). E Pluribus Unum : Diversity and Community in the Twenty‐first Century The 2006 Johan Skytte Prize Lecture. Scandinavian Political Studies. Steven Vertovec. (2007). Super-diversity and its implications, Ethnic and Racial Studies, 30:6, 1024-1054. White, Bob & Marie D. Martel (2021) An Intercultural Framework for Theory and Practice in Third Place Libraries, Public Library Quarterly
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.008 | 0.027 |
| Scholarly communication | 0.020 | 0.024 |
| Open science | 0.004 | 0.016 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".