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Denial of Service Action

2019· other· en· W2944172050 on OpenAlexaff
Molly Sauter

Bibliographic record

VenueThe International Encyclopedia of Media Literacy · 2019
Typeother
Languageen
FieldComputer Science
TopicInternet Traffic Analysis and Secure E-voting
Canadian institutionsMcGill University
Fundersnot available
KeywordsDenialDenial-of-service attackInternet privacyAction (physics)CasualPopularityService (business)Computer securityThe InternetComputer scienceBusinessPsychologyPolitical scienceSocial psychologyLawWorld Wide Web

Abstract

fetched live from OpenAlex

Denial of service actions (DoS) and distributed denial of service actions (DDoS) are broad categories of actions in the online space that involve targeting a server or a service with the intention of rendering it inoperable. These actions generally fall within three broad categories: criminal actions, state‐related or state‐sponsored actions, and activist actions, and can be effected using a wide range of technological means. DDoS actions have become a popular tactic for digital activism, due to their ability to involve many casual participants and the relative ease with which they can be deployed. Activist DoS and DDoS actions are controversial, having been simultaneously compared with respected tactics like sit‐ins and denigrated as censorship or network damage. DDoS actions are likely to grow in popularity as a tactic of activism, criminality, and state aggression, as the Internet becomes progressively normalized as a zone of political action.

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.413
Threshold uncertainty score0.744

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0030.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.264
Teacher spread0.252 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2019
Admission routes1
Has abstractyes

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