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Record W3150064824 · doi:10.29173/iasl7542

Breaking Down Barriers Through the Creation of an International Digital Library for Children

2021· article· en· W3150064824 on OpenAlexvenueno aff
Ann Carlson Weeks, Allison Druin, Benjamin B. Bederson, Juan Pablo Hourcade, Anne C. Rose, Allison Farber, Kara Reuter, Juhyun Lee, Mona Leigh Guha, Yoshi Takayama, Jane White, J Rothschild Anthony, Brewster Kahle

Bibliographic record

VenueIASL Annual Conference Proceedings · 2021
Typearticle
Languageen
FieldComputer Science
TopicICT in Developing Communities
Canadian institutionsnot available
FundersInstitute of Museum and Library ServicesNational Science Foundation
KeywordsThe InternetDigital libraryBrewsterLibrary sciencePolitical scienceFoundation (evidence)Public relationsEngineeringSociologyWorld Wide WebArtComputer scienceLaw

Abstract

fetched live from OpenAlex

A research project, begun in the fall of 2002, expects to tap the potential of the Internet for breaking down barriers and building tolerance and understanding through access to exemplary children’s books from all over the world. The creation of the International Children’s Digital Library (ICDL) is the focus of a five-year project being conducted by the University of Maryland/College Park and the Internet Archive with funding from the US National Science Foundation (NSF) and the Institute for Museum and Library Services (IMLS). This paper describes the project, discusses initial research findings and outlines the direction of ongoing research. Jessica Anthony, and Brewster Kahle

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)0.010
metaresearch head score (Gemma)0.019
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0130.010
Scholarly communication0.0120.016
Open science0.0020.019
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.018
GPT teacher head0.260
Teacher spread0.242 · 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
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
Published2021
Admission routes1
Has abstractyes

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Same venueIASL Annual Conference ProceedingsSame topicICT in Developing CommunitiesFrench-language works237,207