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Record W6996379157

A scientometric approach to communication research: the Marshall McLuhan case

2008· article· en· W6996379157 on OpenAlexaboutno aff

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2008
Typearticle
Languageen
FieldMedicine
TopicNatural Compounds in Disease Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsPortraitRepresentation (politics)Scientific communicationLine (geometry)Scholarly communicationWeb site
DOInot available

Abstract

fetched live from OpenAlex

The application of the Cameo (Characterizations Automatically Made and Edited Online) bibliometric technique -one of the most advanced methodologies for the analysis and representation of information- to the research history of Marshall McLuhan allows us to create a scientific portrait of this Canadian communications expert. The Cameo portrait identifies McLuhan’s professional and academic interests, the authors that most heavily influenced his wave-breaking theories and the evolution of his line of thought in current trends of Communication. By analysing the relational information of citations contained in articles about McLuhan in the ISI Web of Science, we were able to create a map of his intellectual sojourns, including signposts of the most influential authors in his professional career, along with a second representation that shows the “footprints” his writings have left in the world.

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)0.016
metaresearch head score (Gemma)0.056
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.984
Threshold uncertainty score0.226

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.056
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0320.071
Science and technology studies0.0170.022
Scholarly communication0.0160.015
Open science0.0020.006
Research integrity0.0050.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.098
GPT teacher head0.330
Teacher spread0.232 · 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 designNot applicable
DomainEvaluation
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
Published2008
Admission routes1
Has abstractyes

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