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Record W6976777615 · doi:10.6068/dp150633017ad24

Ranking of Countries (2007). United Nations Economic Commission for Europe. Gender Statistics [Archive]: Graduates by Type of Program | Selection 1: Theoretical and advanced research programmes (5A+6) | Selection 2: Both sexes | Selection 3: Graduates, 2007. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 054-003-034.

2015· other· en· W6976777615 on OpenAlexaboutno aff

Bibliographic record

VenueData Planet · 2015
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCommissionRanking (information retrieval)Selection (genetic algorithm)Official statisticsData collectionInternational Standard Industrial ClassificationStatistics educationInternational comparisons

Abstract

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United Nations Economic Commission for Europe (2015). Gender Statistics [Archive]: Graduates by Type of Program | Selection 1: Theoretical and advanced research programmes (5A+6) | Selection 2: Both sexes | Selection 3: Graduates, 2007. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. [Data-file]. Dataset-ID: 054-003-034. Dataset: Shows graduates from higher education programs, by level of program and sex. The Gender Statistics database presents sex-disaggregated social data for the 56 member states of the United National Economic Commission on Europe (UNECE) region, which include the countries of Europe, but also Canada, the United States, Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, Uzbekistan, and Israel. The data covers the Common Gender Indicators for the UNECE region as well as the data series that are used to calculate these indicators. The data have been supplied by national statistical offices through the network of Gender Statistics Focal Points, and are compiled by the Statistical Division of the UNECE Secretariat from different official national and international sources. Data available varies by country. NOTE: Data-Planet discontinued updating of this dataset in 2011 due to irregularities in the data structure. For more recent data on similar topics, please see the Eurostat database. Programs are classified as level 5A or 6 under the International Standard Classification of Education. Level 5A corresponds to tertiary programs that are largely theoretically based and are intended to provide sufficient qualifications for gaining entry into advanced research programs and professions with high skill requirements. Level 6 is reserved for tertiary programs leading to the award of an advanced research qualification. Category: Education, International Relations and Trade Source: United Nations Economic Commission for Europe The United Nations Economic Commission for Europe (UNECE) was established in 1947 as one of the five regional economic commissions of the United Nations. Its major aim is to promote pan-European economic integration. To do so, UNECE brings together 56 countries located in the European Union, non-EU Western and Eastern Europe, South-East Europe and Commonwealth of Independent States (CIS) and North America. All these countries dialogue and cooperate under the aegis of the UNECE on economic and sectoral issues. http://www.unece.org/ Subject: Educational Programs, Gender, Higher Education, Graduates, Educational Attainment

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)0.002
metaresearch head score (Gemma)0.013
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: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.102
Threshold uncertainty score0.332

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0080.038
Science and technology studies0.0010.000
Scholarly communication0.0040.003
Open science0.0020.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0990.115

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 head0.076
GPT teacher head0.406
Teacher spread0.329 · 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
GenreDataset

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
Published2015
Admission routes1
Has abstractyes

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