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Record W1956183446 · doi:10.1002/pa.1475

Do good, goes bad, gets ugly: Kony 2012

2013· article· en· W1956183446 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 Public Affairs · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPoliticsCitizen journalismCompetitor analysisAction (physics)Media studiesSociologyAdvertisingPolitical scienceLawBusinessMarketing

Abstract

fetched live from OpenAlex

With millions of videos with different messages uploaded per year, companies are increasingly looking for means of making their messages stand against competitors. A theory of viral marketing is used to analyze and understand the spread of—and reactions to—a controversial political mega‐viral video, Kony 2012 . Through this analysis, policy makers and marketers could gain a better understanding of how they can use mediums such as YouTube to extend their messages. Kony 2012 concerns the highly publicized leader of a Ugandan guerrilla group, Joseph Kony. The video was a call to action and an attempt to educate the world about the atrocities committed in Sudan. The video was made by an organization called the Invisible Children and created by filmmaker Jason Russell. Following the extraordinary success of Kony 2012, Jason Russell was infamously arrested in San Diego for indecent exposure. The story and video of Russell's arrest and breakdown similarly went viral. The framework that follows analyzes the virality of a political video and the downfall of its creator. Copyright © 2013 John Wiley & Sons, Ltd.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.814
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.279
Teacher spread0.256 · 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