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Record W4378605543 · doi:10.1353/cye.2005.0032

The CYE Journal by the Numbers: Exponential Growth, the Most Popular Articles, and More

2005· article· en· W4378605543 on OpenAlexaboutno aff
The CYE Editors

Bibliographic record

VenueChildren Youth and Environments · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicPoverty, Education, and Child Welfare
Canadian institutionsnot available
Fundersnot available
KeywordsCitationCorporate governanceLibrary sciencePolitical scienceHistoryMedia studiesManagementSociologyLawEconomicsComputer science

Abstract

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Children, Youth and Environments 15(2), 2005 The CYE Journal by the Numbers: Exponential Growth, the Most Popular Articles, and More The CYE Editors Citation: The Editors (2005). “The CYE Journal by the Numbers: Exponential Growth, the Most Popular Articles, and More.” Children, Youth and Environments 15(2): i-viii. Sherry Bartlett offers a thoughtful and stimulating introduction to the papers in this issue, which is dedicated to aspects of children, youth and local governance. Our brief comments here do not address the substance of this topic but describe more prosaic aspects of the CYE journal during the last year. Specifically, we want to share with our readers some numbers concerning access to and use of the journal, outline our plans for future issues, and welcome several new members of the Editorial Advisory Board. The Urchin Traffic Monitor program we have been using since August 2004 to analyze visits on the CYE journal website produces information on the number and date of accesses. It also tells us which countries visitors to the site come from and which pages they access most. The data available for the last 15 months show several interesting results. Accesses to the Journal: Number and Origin First, as illustrated in the chart in Figure 1, the number of journal accesses shows a trend of steady growth. The number of accesses has increased by 500 percent from about 3,000 per month in August 2004 to more than 16,000 in October 2005. On an average day, there are now more than 500 independent visits.1 The CYE Journal by the Numbers: Exponential Growth, the Most Popular Articles, and More ii Figure 1. CYE journal accesses, August 2004- October 2005 CYE Journal Accesses, Aug. 2004 - Oct. 2005 18000 16000 14000 12000 Number of independent accesses by month 10000 8000 6000 4000 2000 0 Month-Year Not only has the number of journal accesses greatly increased, but readers are also coming from more countries now than ever before. The latest count, on November 1, 2005, showed visits from 131 countries, territories and island groups (see Table 1).2 As expected, high-income and Anglophone countries generate the most visits. What comes as a surprise, though, is the strong presence of many low-income countries. While access to the Internet has improved in the developing regions of the world, serious constraints remain in many places. The number of accesses by readers from these regions provides testimony to relevant article content and indicates that the journal serves a need that goes well beyond more affluent English-speaking nations. In this light, we seek to maintain and, if possible, further widen the international reach of the CYE Editorial Advisory Board (see below). Figure 2. Origin of visits to CYE journal web site Origin of Visits to CYE Journal Web Site (in order of frequency) 1 USA 45 Peru 89 Ecuador 2 United Kingdom 46 Romania 90 Zambia 3 Australia 47 Russian Federation 91 Georgia 4 Canada 48 Pakistan 92 Namibia 5 Netherlands 49 Bahrain 93 United Arab Emirates 6 South Africa 50 Vietnam 94 Nicaragua 7 Germany 51 Jordan 95 Kuwait The CYE Journal by the Numbers: Exponential Growth, the Most Popular Articles, and Moreiii 8 Belgium 52 China 96 Bahamas 9 Singapore 53 Trinidad and Tobago 97 Lesotho 10 Italy 54 Chile 98 Kazakhstan 11 Japan 55 Lithuania 99 Bermuda 12 New Zealand 56 Cyprus 100 Christmas Island 13 India 57 Slovak Republic 101 Bolivia 14 Sweden 58 Fiji 102 Macedonia 15 Norway 59 Morocco 103 Nigeria 16 Turkey 60 Lebanon 104 Belarus 17 Finland 61 Croatia 105 Madagascar 18 Israel 62 Zimbabwe 106 Bosnia-Herzegovina 19 Portugal 63 Tanzania 107 Sri Lanka 20 Denmark 64 Slovenia 108 Ghana 21 Switzerland 65 Yugoslavia 109 Niue 22 France 66 Ukraine 110 Dominica 23 Mexico 67 Iran 111 Algeria 24 Malaysia 68 Ethiopia 112 Virgin Islands 25 Greece 69 Botswana 113 Cook Islands 26 Philippines 70 Dominican Republic 114 Kyrgyz Republic 27 Brazil 71 Latvia 115 Uganda 28 Indonesia 72 Kenya 116 Syria 29 Ireland 73 Brunei Darussalam 117 Burkina Faso 30 Thailand 74 Mozambique 118 Mongolia 31 Poland 75 Costa Rica 119 El Salvador 32 Austria 76 Mauritius 120 Bhutan 33...

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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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.187
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.007
GPT teacher head0.214
Teacher spread0.207 · 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 teacher head, not a consensus.

Study designObservational
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
Published2005
Admission routes1
Has abstractyes

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