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Record W2919142803 · doi:10.5539/ijel.v9n2p353

A Study on Persuasive Language in Personal Selling

2019· article· en· W2919142803 on OpenAlexvenueno aff
Danyan Huang

Bibliographic record

VenueInternational Journal of English Linguistics · 2019
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsnot available
FundersGuangdong University of Foreign Studies
KeywordsPersuasionAdaptation (eye)Personal sellingAdvertisingPsychologyProcess (computing)MarketingBusinessSociologySocial psychologyComputer science

Abstract

fetched live from OpenAlex

The present study, which is qualitative in nature, is an investigation into the persuasive language used in the interactive communication of personal selling based on Jef Verschueren’s linguistic Adaptation Theory and some important ideas of Game Theory. Within the framework of these theories, four personal selling cases were analyzed to reveal the interactive process of selling between the seller and the buyer as if they were engaged in a game in which the former used various persuasion strategies in different stages of selling to adapt to the physical, social and mental world of the latter. The two successful cases revealed that the seller’s sound adaptation to the three worlds of the buyer ultimately helped him/her to achieve a win-win situation while the two unsuccessful ones showed that the failure to adapt to any one of the three worlds led to a failed selling attempt and unproductive interaction between the two parties.

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)0.000
metaresearch head score (Gemma)0.009
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 score0.128
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.333
Teacher spread0.312 · 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

Citations6
Published2019
Admission routes1
Has abstractyes

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