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Record W4395072082 · doi:10.32388/e8r33i

Formation and Development of Journalism in the System of Social Communications Canada, Mexico, Guatemala and Cuba

2024· preprint· en· W4395072082 on OpenAlexaboutno aff
Олександр Холод

Bibliographic record

VenueQeios · 2024
Typepreprint
Languageen
FieldComputer Science
TopicMedia and Digital Communication
Canadian institutionsnot available
Fundersnot available
KeywordsJournalismPolitical scienceGeographyEconomic growthMedia studiesTelecommunicationsSociologyEngineeringEconomics

Abstract

fetched live from OpenAlex

This study explores the formation and development of journalism within the social communications system across Canada, Mexico, Guatemala, and Cuba, emphasizing the distinctive historical and cultural contexts that shape journalistic practices in these nations. Canadian journalism is influenced by its multicultural and multilingual environment, technological advancements, and issues related to accessibility and archival sources. In Mexico, historical complexities, such as the pre-Hispanic period and colonial impacts, play a significant role. Guatemala’s journalism is marked by its indigenous languages and the effects of a prolonged civil war on social communications. Cuban journalism, however, is heavily dictated by socialist policies, focusing on state-controlled media and the professional training of journalists. This comparative analysis reveals diverse trajectories in the evolution of journalism and social communication, driven by unique socio-political and cultural dynamics in each country

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)0.001
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.094
Threshold uncertainty score0.242

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.005
Science and technology studies0.0090.004
Scholarly communication0.0060.001
Open science0.0010.003
Research integrity0.0000.001
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 head0.047
GPT teacher head0.274
Teacher spread0.227 · 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
GenreOther

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

Citations1
Published2024
Admission routes1
Has abstractyes

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