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Record W4399201681 · doi:10.7764/cdi.58.69481

Explorando el contexto laboral de la academia de la comunicación organizacional en América Latina

2024· article· es· W4399201681 on OpenAlexaff
Lissette Marroquín Velásquez, Gabriela Rabello de Lima, María-de-Jesús Montoya-Robles

Bibliographic record

VenueCuadernos de información · 2024
Typearticle
Languagees
FieldSocial Sciences
TopicAdvertising and Communication Studies
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesPersonaPolitical scienceSociologyArt

Abstract

fetched live from OpenAlex

The labour context of Latin American organizational communication scholars is presented based on an empirical study that explores the dimensions of well-being at work, institutional demands, resources, and research activities. We developed a questionnaire for this purpose. The data collection took place between May 2019 and April 2021. It was answered by 81 researchers from 14 Latin American countries. The results of the survey showed that researchers face significant challenges related to resources and research support. Moreover, the job demands’ level and perceived well-being varies more according to gender. Thus, the article expands the understanding of the reality of Latin American organizational communication scholars, identifying key issues such as the impact of their working conditions and the inclusion challenges they face.

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)0.006
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.142

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0090.011
Scholarly communication0.0140.006
Open science0.0010.007
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.032
GPT teacher head0.423
Teacher spread0.391 · 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 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

Citations2
Published2024
Admission routes1
Has abstractyes

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