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Record W4283209786 · doi:10.6017/ital.v41i2.15161

Gathering Strength to Combat Access Inequality

2022· article· en· W4283209786 on OpenAlexaboutno aff
Julie Lane

Bibliographic record

VenueInformation Technology and Libraries · 2022
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsPublic accessOrder (exchange)InequalityPublic relationsLibrary scienceSociologyPolitical scienceComputer scienceBusinessMathematics

Abstract

fetched live from OpenAlex

Nestled on the northern edge of Lake Ontario, Prince Edward County is home to a six branch public library system that is proud to have created a robust and vibrant relationship with the local school board. Through the lens of access, this article explores the steps taken by the public library to create meaningful connections with administrative staff on the school board level in order to bring practical training and resources to teachers and students in order to enhance and support their learning.

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)0.008
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.049
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0110.013
Scholarly communication0.0120.009
Open science0.0010.026
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0230.002

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 head0.118
GPT teacher head0.428
Teacher spread0.310 · 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 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

Citations1
Published2022
Admission routes1
Has abstractyes

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