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Cyber Law and Cyber Security Policies in Pakistan: A Comparative Study with USA, Canada and Australia

2024· article· en· W4394825588 on OpenAlexaboutno aff
Omer Mahmood Watto, Muhammad Islam, Syed Arshad Hussain, Muhammad Shahab

Bibliographic record

VenuePakistan Journal of Humanities and Social Sciences · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCybersecurity and Cyber Warfare Studies
Canadian institutionsnot available
Fundersnot available
KeywordsResilience (materials science)GeopoliticsCyber threatsContext (archaeology)CyberwarfarePolitical scienceBusinessComputer securityLawGeographyComputer sciencePolitics

Abstract

fetched live from OpenAlex

This study evaluates cyber-law and security policies in Pakistan, the USA, Canada, and Australia, exploring how each country's geopolitical and socioeconomic context influences its cyber-defense and lawful measures against cyber threats. It compares their policies to find out best practices and gaps, aiming to guide the creation of stronger, more adaptable cyber-policies. The research emphasizes the importance of comprehensive legal frameworks to protect against emerging cyber threats and the vital role of international collaboration in enhancing global cyber resilience.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.218

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0100.002
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.064
GPT teacher head0.375
Teacher spread0.310 · 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 designNot applicable
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

Citations1
Published2024
Admission routes1
Has abstractyes

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