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Record W2008693071 · doi:10.1108/03074800510587354

Participation in the global knowledge commons

2005· article· en· W2008693071 on OpenAlexaff
Leslie Chan, Sely Costa

Bibliographic record

VenueNew Library World · 2005
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsDeveloping countryInteroperabilityOriginalityDisseminationPublic relationsBusinessPublishingInformation DisseminationKnowledge sharingKnowledge managementCommonsPolitical scienceEconomic growthComputer scienceWorld Wide WebEconomics

Abstract

fetched live from OpenAlex

Purpose This paper aims to provide a review of recent trends in the open access (OA) movement, as well as to discuss the significance of those trends for information access in developing countries. Design/methodology/approach An analysis of the recent literature was carried out, focusing on the benefits of a greater information access in developing countries. The paper also brings together the diverse experiences from the authors on OA publishing and archiving with institutions in a number of developing countries. Findings Knowledge workers in developing countries are now getting access to scholarly and scientific publications and electronic resources at a level that is unmatched historically. This is highly significant, if developing countries are to meet the millennium development goals. The OA movement and the growing number of Open Archive Initiative‐compliant institutional repositories promise to provide even greater access to resources and publications that were previously inaccessible. These low cost technology and interoperability standards are providing great opportunities for libraries and publishers in developing countries to disseminate local research and to bridge the south‐north knowledge gap. Originality/value This paper therefore provides recommendations for knowledge workers on how to actively participate in and contribute to the global knowledge commons. The results and recommendations contained in the paper should be of interest to authors, policy makers, funding agencies and information professionals in both developing and developed countries.

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)0.017
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Open science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.998
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.006
Science and technology studies0.0060.014
Scholarly communication0.0220.015
Open science0.0020.025
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0160.001

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 head0.560
GPT teacher head0.587
Teacher spread0.027 · 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 designTheoretical or conceptual
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

Citations165
Published2005
Admission routes1
Has abstractyes

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