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Record W3093745611

A bibliometrics analysis of Canadian electrical and computer engineering institutions based on IEEE journal publications (1996-2006)

2012· article· en· W3093745611 on OpenAlexaffabout
Vahid Garousi, Tan Varma

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsComputer scienceBibliometricsData scienceLibrary science
DOInot available

Abstract

fetched live from OpenAlex

This paper presents a bibliometric assessment of Canadian institutions in the discipline of Electrical and Computer Engineering (ECE) from 1996 to 2006. The paper is a first step in identifying the top institutions over a 10-year period in Canada. The rankings are calculated using three metrics: (1) simple count of papers, (2) journal impact factors, and (3) journal impact factor of each institution normalized by its faculty size. The venues/journals considered are 71 flagship IEEE Transaction journals in different areas of ECE which are perceived as the most prestigious venues in the discipline. Using the three metrics, the top-ranked institutions are identified as: the University of Waterloo (by two metrics), and Queen’s University’s (by one metric). Our study also reveals other interesting results, such as: (1) Researchers from the universities of Waterloo and Toronto, combined, authored about a third of all the Canadian papers published in the IEEE Transaction journals during the time period under study (691 of 2,540 papers). (2) Canadian provinces have different levels of ECE research productivity and efficiency, and (3) ECE ranking of the Canadian institutions has similarities and differences versus a recently-published software engineering ranking of the same institutions. While this study is in the context of Canadian ECE institutions, our approach can be easily adapted to rank the institutions of any other nation and/or in any other discipline.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: yes · About a Canadian topic: yes
Observationalhigh
gptBibliometricsScholarly communication
Domain: not available · Genre: Empirical
About the Canadian research system: yes · About a Canadian topic: yes
Other designhigh
models splitAgreement compares identical category sets and study designs across arms.

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 categoriesBibliometrics, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.757
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0260.005
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.057
GPT teacher head0.253
Teacher spread0.196 · 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

Labeled directly by 2 models reading the full record.

BibliometricsScholarly communication

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational · Other design
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
Published2012
Admission routes2
Has abstractyes

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