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Record W2906794223 · doi:10.1177/1532673x18821954

Partisan Bias in Economic News Content: New Evidence

2018· article· en· W2906794223 on OpenAlex
Eric Merkley

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAmerican Politics Research · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicMedia Influence and Politics
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsTone (literature)MainstreamDemocracyInflation (cosmology)Media biasUnemploymentEconomicsEmpirical evidencePolitical sciencePoliticsLawMacroeconomics

Abstract

fetched live from OpenAlex

Claims that the mainstream media are biased in favor of the Democratic Party are commonplace. However, empirical research has yielded mixed results and neglected potential bias in the dynamics of media behavior. This article contributes to this literature by using time series analyses of the dynamics in media tone based on more than 400,000 stories on inflation and unemployment from top-circulating American print media and the Associated Press newswire. The results suggest there is bias in favor of Democratic presidents. Media tone in unemployment and inflation coverage is more favorable during Democratic presidencies after controlling for economic performance. Tone is also generally more responsive to negative, short-term changes in economic conditions during Republican presidencies. In other words, bias is stronger with worsening economic conditions.

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)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.825
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.005
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.003

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 head0.649
GPT teacher head0.563
Teacher spread0.086 · 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