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Record W3111481502 · doi:10.1177/0276146720978257

Consumer Choicemaking and Choicelessness in Hyperdigital Marketspaces

2020· article· en· W3111481502 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 Macromarketing · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicArt History and Market Analysis
Canadian institutionsYork University
Fundersnot available
KeywordsConsumption (sociology)Consumer choiceHappeningAutonomyThe InternetMacroPerceptionBusinessMarketingSociologyComputer sciencePolitical scienceEpistemologySocial scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Technologies, especially Internet-based digital ones, are reshaping choice processes – actual considerations and actions, as well as perceptions of these – in massive, often fundamental, ways. In this paper, our goal is to explore choice processes in general, and especially choice processes in hyperdigital marketspaces (i.e., with massively, pervasively interconnected things) with examples drawn from U.S. macro consumption contexts. We start with a short review of discourses on choice and choicelessness and then shift to the emerging era of technology-shaped choice processes that are especially observable in contemporary hyperdigital marketspaces. For the increasingly large swaths of market segments that consume, indeed live, digitally, we find deft symbolic sublimations and inversions happening, wherein manipulation is perceived as autonomy enhancing.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.913
Threshold uncertainty score0.873

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.026
GPT teacher head0.209
Teacher spread0.182 · 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