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Record W4404468642 · doi:10.1080/0267257x.2024.2425691

Is that JPEG worth 70 million dollars? Value creation and perceptions of nonfungible tokens in a bubble economy

2024· article· en· W4404468642 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 Marketing Management · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsYork University
FundersResearch Grants Council, University Grants Committee
KeywordsValue (mathematics)PerceptionBusinessEconomic bubbleMarketingValue creationBubbleCommerceEconomicsAdvertisingFinanceComputer sciencePsychologyMathematicsStatistics

Abstract

fetched live from OpenAlex

Non-fungible tokens (NFTs) have sparked questions about value. In our attempt to shed light on the value of NFTs, especially during their dramatic rise in the early 2020s, we develop a theoretical analysis of the extrinsic factors shaping NFT value based on a perfect storm of individual, social, marketing, and environmental factors. After detailing the effects of each of these factors in shaping NFT valuation, we develop a new understanding of value in a frenzy of celebrity influence, social media, decentralized authority, unregulated markets, marketing hype, and media magnification. We also articulate the intrinsic factors that still affect value as well. We argue that in the NFT bubble economy and its aftermath, extrinsic, social, and situational factors came to dominate valuation. We offer advice on how to make sense of value in the post NFT bubble and outline a research agenda that considers the role of cryptocurrency and metaverse.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.544
Threshold uncertainty score0.607

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.019
GPT teacher head0.259
Teacher spread0.240 · 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