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Numeracy Programming at Major Canadian Urban Libraries: An Exploratory Study

2020· article· en· W3027020392 on OpenAlexaffvenueabout
Andrea Budac, Céline Gareau-Brennan, David Mucz, Michael B McNally, Dinesh Rathi

Bibliographic record

VenuePartnership The Canadian Journal of Library and Information Practice and Research · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Administration
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNumeracyExploratory researchLiteracyGovernment (linguistics)Adult literacyComputer scienceMathematics educationPsychologySociologyPedagogySocial science

Abstract

fetched live from OpenAlex

The Government of Canada identifies numeracy as a foundational skill for work, learning, and life. Libraries have historically been champions of literacy; however, the role of libraries in developing numeracy skills is understudied. Specifically, there is a critical gap in studying numeracy programs offered by public libraries. This exploratory study examines the state of numeracy programming at five major urban public libraries in Canada (Calgary Public Library, Edmonton Public Library, Bibliothèques de Montréal, Ottawa Public Library, and Toronto Public Library) to understand the types and varieties of numeracy programs that they offer. The frequency of programs, the intended age range, and the program content are the main foci of this paper. The researchers examined 1166 program listings by scraping programming information from the five libraries’ websites. The data was collected for the second week of December 2015 and relied on programming descriptions from libraries' websites. Results showed that a total of 65 programs (5.6% of total programs) covered numeracy related skills. Overall, the options to learn about numeracy concepts were very limited at all of the libraries in the sample. Calgary offered the highest number of children-focused numeracy programs, while Toronto offered the greatest number of adult-focused numeracy programs. “Math/mathematics” was the most common term used to describe numeracy-related programs. This exploratory study underscores the need for greater investigation of numeracy programming in public libraries.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.705
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0030.085
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.125
GPT teacher head0.372
Teacher spread0.247 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2020
Admission routes3
Has abstractyes

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