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Record W2239409977 · doi:10.1139/cjce-2015-0127

Bibliometric analysis of research in international construction

2016· article· en· W2239409977 on OpenAlexvenueno aff
Selin Gündeş, Güzin Aydoğan

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2016
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsScopusCompetition (biology)ProductivityRegional scienceInternational marketDistribution (mathematics)Political scienceBusinessEconomicsInternational tradeSociologyEconomic growthMathematics

Abstract

fetched live from OpenAlex

There has been increasing interest in international construction since the late 1990s due to growing competition in global markets. A bibliometric analysis of international construction research is conducted to evaluate the trends and to map the productivity in the field. Using the Scopus database from 2003 to 2013; document type, research performance of leading journals and authors, geographic and institutional distribution of research is assessed. The core and sub topics of the literature is also analyzed to determine critical themes in international construction. Results reveal that (1) risk management, (2) measuring performance, (3) general strategy and (or) competitiveness, and (4) foreign market entry decision are the top four core themes in international construction research. The fluctuations in the number of papers in different subject categories reflect the new tendency in international construction debate, which emphasizes a shift from measuring performance themes to general strategy and (or) competitiveness and foreign market entry decision in international construction.

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 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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics, Insufficient payload (model declined to judge)
Consensus categoriesBibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.177
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.2870.145
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.099
GPT teacher head0.370
Teacher spread0.271 · 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; both teacher heads agree on what is shown here.

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

Citations19
Published2016
Admission routes1
Has abstractyes

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