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‘May Be a Picture of a Dog and a Book’: The Inaccessibility of Public Library Social Media Feeds

2023· article· en· W4383216425 on OpenAlexaffvenueabout
Heather Hill, Kevin Oswald

Bibliographic record

VenuePartnership The Canadian Journal of Library and Information Practice and Research · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Administration
Canadian institutionsWestern University
Fundersnot available
KeywordsSocial mediaOrder (exchange)Public relationsSociologyPolitical scienceWorld Wide WebMedia studiesLibrary scienceComputer scienceBusiness

Abstract

fetched live from OpenAlex

This research investigates the accessibility of Ontario public libraries’ social media feeds. Social media plays an important role in how public libraries engage with their communities. This patron engagement outside of library-maintained websites, raises questions around accessibility for persons with disabilities. Given the increasing usage of social media as a communication mechanism, how accessible are Ontario public library social media feeds? Of specific interest here is the use of alternative text (alt text) attributed to images posted on Ontario public libraries’ social media posts. Findings indicate a dearth of alt text on social media feeds. Suggestions are made for creating good alt text in order to create a more equitable environment.

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)0.007
metaresearch head score (Gemma)0.046
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.989
Threshold uncertainty score0.532

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.046
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0100.009
Scholarly communication0.0110.012
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0170.002

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.

Opus teacher head0.159
GPT teacher head0.403
Teacher spread0.244 · 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.

Study designQualitative
Domainnot available
GenreEmpirical

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

Citations5
Published2023
Admission routes3
Has abstractyes

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