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Record W4321153537 · doi:10.1093/jcr/ucad013

The Emergence and Evolution of Consumer Language Research

2023· article· en· W4321153537 on OpenAlex

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

VenueJournal of Consumer Research · 2023
Typearticle
Languageen
FieldComputer Science
TopicDigital Communication and Language
Canadian institutionsYork University
Fundersnot available
KeywordsKey (lock)Consumer researchService (business)Work (physics)SociologyPsychologyComputer scienceAdvertisingMarketingBusinessEngineering

Abstract

fetched live from OpenAlex

Abstract Over the last 50+ years, there has been a huge rise in interest in consumer language research. This article spotlights the emergence and evolution of this area, identifying key themes and trends and highlighting topics for future research. Work has evolved from exploration of broad language concepts (e.g., rhetorics) to specific linguistic features (e.g., phonemes) and from monologues (e.g., advertiser to consumer) to two-way dialogues (e.g., consumer to service representative and back). We discuss future opportunities that arise from past trends and suggest two important shifts that prompt questions for future research: the new shift toward using voice (vs. hands) when interacting with objects and the ongoing shift toward using hands (vs. voices) to communicate with people. By synthesizing the past, and delineating a research agenda for the future, we hope to encourage more researchers to begin to explore this burgeoning area.

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)0.011
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.651
Threshold uncertainty score0.380

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
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 head0.137
GPT teacher head0.454
Teacher spread0.318 · 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