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Record W4281751857 · doi:10.29173/pathfinder52

Public Libraries and the Social Inclusion of Homeless People: A Literature Review

2022· review· en· W4281751857 on OpenAlexaffvenueabout
Melanie Forrest

Bibliographic record

VenuePathfinder A Canadian Journal for Information Science Students and Early Career Professionals · 2022
Typereview
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsInclusion (mineral)Public relationsContext (archaeology)SociologyPolitical scienceSocial scienceGeography

Abstract

fetched live from OpenAlex

Public libraries have an ethical and professional responsibility to create an inclusive and welcoming environment for their entire patron community, including those individuals experiencing homelessness, in part by providing equal and equitable access to information and library services. This literature review examines the small but growing body of LIS literature—both internationally and in the Canadian context—on the self-reported informational and social needs of people experiencing homelessness, and their use of public libraries. Key findings reveal that while some homeless people use public library spaces to meet basic physiological needs, most visit public libraries for many of the same reasons as their housed counterparts. Importantly, homeless library users indicated that spending time at the library contributed to their sense of belonging and social inclusion. The literature also demonstrated a clear trend toward partnerships between public libraries and professional support agencies to better address patrons’ needs. Services relevant to homeless people should be developed in consultation or collaboration with this target group to ensure that resulting recommendations are appropriate to their needs, reduce or remove barriers to equal access, and contribute positively to social inclusion.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.026
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0100.013
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.131
GPT teacher head0.452
Teacher spread0.321 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations9
Published2022
Admission routes3
Has abstractyes

Explore more

Same venuePathfinder A Canadian Journal for Information Science Students and Early Career ProfessionalsSame topicHomelessness and Social IssuesFrench-language works237,207