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Record W3148457967 · doi:10.29173/iasl7834

School Library eBook Providers and Linguistic Equity

2021· article· en· W3148457967 on OpenAlexvenueno aff
Andrea Paganelli, Cynthia Houston

Bibliographic record

VenueIASL Annual Conference Proceedings · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsnot available
Fundersnot available
KeywordsLinguistic diversityPurchasingDiversity (politics)Equity (law)PopulationLibrary scienceDigital libraryComputer sciencePublic relationsWorld Wide WebBusinessSociologyPolitical scienceLinguisticsMarketing

Abstract

fetched live from OpenAlex

If school library collections must meet the needs of the communities they serve, the native languages of the student population must be an important consideration when making purchasing decisions about eBooks. Many professionals in the library community believe that materials in electronic format have the potential to enrich library collections with linguistic diversity. To ensure that school library collections reflect the linguistic diversity of the community, as school library professionals we need to gain a better understanding of what resources are available for our students in digital format. Recent studies indicate that eBooks available from vendors to schools libraries do not meet the linguistic needs of children whose native language is not English. Several international organizations have recognized this issue and are developing initiatives to resolve the growing digital and linguistic divide.

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)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.991
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0050.006
Scholarly communication0.0090.010
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0220.001

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 head0.028
GPT teacher head0.303
Teacher spread0.275 · 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 designNot applicable
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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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