MétaCan
Menu
Back to cohort
Record W2128202605 · doi:10.1504/ijtmkt.2014.058085

Generation-C: creative consumers in a world of intellectual property rights

2013· article· en· W2128202605 on OpenAlexaff
Jan Kietzmann, Ian O. Angell

Bibliographic record

VenueInternational Journal of Technology Marketing · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsIntellectual propertyLegislationBusinessLaw and economicsProperty rightsPublic relationsLawSociologyPolitical science

Abstract

fetched live from OpenAlex

Generation-C is a generational movement consisting of creative consumers, those who increasingly modify proprietary offerings, and of members of society who in turn use the developments of these creative consumers. It is argued that their respective activities, creating and using modified products, are carried out by an increasing number of people, everyday, without any moral and legal considerations. The resulting controversies associated with existing intellectual property rights are discussed, and suggestions put forward that the future can only bring conflict if such legislation is not changed so that derivative innovations are allowed to flourish. The article concludes with important messages to organisations, intellectual property rights lawyers, owners of property rights, governments and politicians, suggesting they reconsider their respective stances for the good of society.

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)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.010
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.013
Scholarly communication0.0100.010
Open science0.0010.006
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0080.001

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 head0.024
GPT teacher head0.303
Teacher spread0.279 · 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 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

Citations8
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Technology MarketingSame topicDigital Marketing and Social MediaFrench-language works237,207