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Record W3167172560 · doi:10.21810/jicw.v3i3.2809

Gen Z as Security Content Creators: Recreating the Terms of the Social Contract

2021· article· en· W3167172560 on OpenAlexvenueno aff
Natalie Archutowski, Serge Bergler

Bibliographic record

VenueThe Journal of Intelligence Conflict and Warfare · 2021
Typearticle
Languageen
FieldComputer Science
TopicPersona Design and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsFraming (construction)NarrativePresentation (obstetrics)Media studiesContent (measure theory)SociologyPolitical scienceComputer securityEngineeringComputer scienceArtLiteratureCivil engineeringMathematics

Abstract

fetched live from OpenAlex

On November 27, 2020, Natalie Archutowski and Serge Bergler presented on the topic of Generation Z (Gen-Z) as security content creators, at the 2020 CASIS West Coast Security Conference. The presentation was followed by a question and answer period. Key points of discussion included: Narrative control, framing and influencer activity, generational differences, ethics, and what role gen-z plays.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.624
Threshold uncertainty score0.340

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.064
GPT teacher head0.307
Teacher spread0.242 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2021
Admission routes1
Has abstractyes

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