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Record W1863873288

Valor del consumidor y modos de recepción de medios: respuestas de la audiencia Ryan, un pequeño documental psicorrealista animado por computador, y su propia documentación en Alter Egos

2010· article· es· W1863873288 on OpenAlexaff
Charles H. Davis, Florin Vladica

Bibliographic record

VenueIntellectum (Universidad de La Sabana) · 2010
Typearticle
Languagees
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsProduct (mathematics)Context (archaeology)Value (mathematics)AnimationArtAdvertisingSociologyVisual artsComputer scienceHistoryBusiness
DOInot available

Abstract

fetched live from OpenAlex

Consumer value and value creation are fundamental con-cepts in marketing, management and in literature on orga-nizations, but are almost never considered in the context of screen-based “experience” products. In this paper, the au-thors depart from the prevailing approaches to audience or reception studies by investigating the experience value the consumption of a screen-based product has for the specta-tor. Using the Q-methodology and Holbrook’s consumer value framework (1999), they empirically identify audience segments based on television viewers’ subjective experi-ence with an innovative flm product: the award-winning, computer-animated short documentary Ryan. The flm uses creative state-of-the art animation to tell a compelling story in ways that stretch the documentary genre. The authors uncover and describe four audience segments. Unexpect-edly, these four segments bear a strong resemblance to the four principal modes of media reception proposed recent-ly by Michelle (2007), thereby creating a potentially fruit-ful link between the framework for consumer experience value and media reception studies

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.298
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.007
GPT teacher head0.272
Teacher spread0.265 · 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 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
Published2010
Admission routes1
Has abstractyes

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