MétaCan
Menu
Back to cohort
Record W7039534088

Mind & Matter: the Discursive Construction of the iPhone in Apple's Advertising

2014· article· en· W7039534088 on OpenAlexfundno aff

Bibliographic record

VenueUWM Digital Commons (University of Wisconsin–Milwaukee) · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicMedia, Communication, and Education
Canadian institutionsnot available
FundersYork University
KeywordsConstruct (python library)Agency (philosophy)Reflection (computer programming)Online advertisingMarket researchUser Research
DOInot available

Abstract

fetched live from OpenAlex

The widespread adoption of smartphone technology in the contemporary United States requires critical reflection on its role within society. This thesis compares the way Apple's television advertising discourse, from 2007 to 2011, frames the iPhone to consumers with the way Apple's iAd promotional material frames the iPhone to advertisers, and considers what the disparity between these two frameworks says about the still-evolving role of smartphone technology in society. It argues that the disparity between these two frameworks is indicative of a fundamental tension within smartphone technology. This tension is reflected in Apple's ability to discursively construct the iPhone as a tool of user empowerment, while at the same time discursively constructing the iPhone as a sophisticated market research and advertising platform. This study shows that user agency is complicated by the iPhone's technical design which produces information about the user in an effort to modify their behavior for commercial purposes.

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)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0100.049
Scholarly communication0.0130.009
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.232
Teacher spread0.218 · 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 designQualitative
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
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueUWM Digital Commons (University of Wisconsin–Milwaukee)Same topicMedia, Communication, and EducationFrench-language works237,207