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Record W4388267221 · doi:10.22533/at.ed.2163282313103

CHALLENGES OF LABORATORY PRODUCTION IN JOURNALISM IN YEAR I OF THE COVID-19 PANDEMIC. REPORT AND EXPERIMENTS

2023· article· en· W4388267221 on OpenAlex
Marcelo Luciano Martins Di Renzo

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueScientific Journal of Applied Social and Clinical Science · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsWorld Federation of Science Journalists
Fundersnot available
KeywordsPandemicCoronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakJournalismProduction (economics)Political scienceVirologyMedicineOutbreakEconomicsLawInfectious disease (medical specialty)Pathology

Abstract

fetched live from OpenAlex

Report on the impact caused by the Covid-19 pandemic and the consequent adoption of remote teaching in the practical subjects Printed Journalism Laboratory Project and Radiojournalism Laboratory Project in the Journalism Course at the ``Universidade Catlica de Santos``, from March 2020.Focuses on the challenges caused by the transition in pedagogical dynamics, the lack of accessibility, social isolation and trauma caused by the disease, as well as the alternatives for overcoming it.

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.

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)0.019
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.293
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0190.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.626
GPT teacher head0.550
Teacher spread0.076 · 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