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Record W2550712588 · doi:10.1177/2057047316679418

On the transactional ecosystems of digital media

2016· article· en· W2550712588 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

VenueCommunication and the Public · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDigital Platforms and Economics
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsTransactional leadershipConvergence (economics)PaymentMobile paymentDigital currencyDatabase transactionMobile deviceComputer scienceCurrencyTechnological convergenceEconomicsTelecommunicationsWorld Wide WebManagement

Abstract

fetched live from OpenAlex

This article contributes a framework for understanding the convergence of two ‘transactional ecosystems’ or, put differently, the convergence of two types of currency: money and attention. The former is represented in the push to make commercial transactions ubiquitous and seamless (e.g. as in mobile payment systems), while the latter is represented by theories of the ‘attention economy’ and subsumed in the ‘attention and engagement’ metrics that currently shape the production and distribution of content on digital and mobile platforms. The means of communication and commerce, of payment and attention, are increasingly wedded together in the same device or platform implying that how we pay for things is bound up with ‘the things to which we attend’. Drawing on literature on the political economy of media, this article provides historical and theoretical contexts for this convergence, offers some paradigmatic examples alongside industry analysis and concludes by raising potential concerns emerging from its current trajectory.

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)0.000
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.264
Threshold uncertainty score0.425

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
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 head0.028
GPT teacher head0.182
Teacher spread0.154 · 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