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Record W35777904 · doi:10.1016/j.jare.2021.11.002

Seminal Exchanges: Exchanges that Change Our Life

2011· article· en· W35777904 on OpenAlexfundno aff
Stephen Fanning

Bibliographic record

VenueJournal of Advanced Research · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsSituational ethicsConsumption (sociology)MarketingProduct (mathematics)Qualitative researchProcess (computing)BusinessAdvertisingPsychologyComputer scienceSocial psychologySociologyMathematics

Abstract

fetched live from OpenAlex

The purpose of this paper is to revisit and advance a classic marketing concept; Copeland‟s (1923) classification of convenience, specialty and shopping exchanges. In doing so, product involvement, the three time zones of the buyer decision process and the three estimation, assessment and evaluation qualities, are also discussed. The findings are the result of a larger interpretive, qualitative study that explored a number of classic marketing concepts through the consumption experiences of a group of immigrant consumers. In this paper a new classification – seminal exchanges is proposed. Seminal exchanges have distinguishing features (1) they are high in total involvement; that means high in situational, response and enduring involvement (2) they place a marker in a person‟s life; a life before an exchange and a life after an exchange, and (3) they influence future consumption activities to a greater degree than convenience, shopping or specialty products.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.054
Threshold uncertainty score0.181

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.023
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0120.014
Scholarly communication0.0160.020
Open science0.0020.014
Research integrity0.0050.010
Insufficient payload (model declined to judge)0.0540.021

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 head0.488
GPT teacher head0.400
Teacher spread0.088 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2011
Admission routes1
Has abstractyes

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