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Record W4399970641 · doi:10.1386/jams_00123_1

COVID-19 induced changes to news gathering and news production: Practical experiences from five Ghanaian newsrooms

2024· article· en· W4399970641 on OpenAlexaff
Manfred Kofi Antwi Asuman, Noel Nutsugah, Redeemer Buatsi, Theophilus Peculiar

Bibliographic record

VenueJournal of African Media Studies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicMedia Studies and Communication
Canadian institutionsWestern University
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakPolitical scienceSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Production (economics)AdvertisingMedia studiesSociologyBusinessEconomicsMedicineVirology

Abstract

fetched live from OpenAlex

This study, grounded in Kurt Lewin’s theory of change management, investigates how the COVID-19 pandemic influenced change in the news gathering and news production process in five newsrooms in Ghana. Through semi-structured in-depth interviews, our study proves that the social restrictions that were introduced due to the COVID-19 pandemic forced Ghanaian newsrooms to introduce certain measures, including work-from-home policies, a strategy that had never been explored prior to the pandemic. Our study further reveals that, whereas male journalists were usually given tasks that were considered dangerous, such as reporting from the morgue and intensive care units of hospitals, female journalists were usually assigned news conferences and tasked to conduct interviews with various stakeholders, a gender perspective to news gathering during the pandemic which has never been reported. Based on these and other findings, we argue that the COVID-19 pandemic did indeed drive change in how journalists gather and produce news.

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 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)0.001
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.395
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.144
GPT teacher head0.413
Teacher spread0.269 · 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 teacher head, not a consensus.

Study designQualitative
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
Published2024
Admission routes1
Has abstractyes

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