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Record W4411396708 · doi:10.53762/qn1nzp64

10.53762/qn1nzp64

2000· article· en· W4411396708 on OpenAlexvenueno aff
Abaid Ullah Anwar, Naveed Ali Shah

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicPolitics and Conflicts in Afghanistan, Pakistan, and Middle East
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsPolitical scienceState (computer science)Civil societyDemocracyLanguage changePolitical economyContext (archaeology)Sustainable developmentPublic administrationEconomicsLaw

Abstract

fetched live from OpenAlex

Electoral politics has long been a dominant feature of Pakistan's political landscape, with political parties vying for power through democratic means. However, this approach has often led to short-term thinking and a lack of focus on sustainable development. This paper explores the challenges and prospects of transitioning from electoral politics to sustainable politics in Pakistan. It examines the current political, economic, and social context of the country, including the role of the military, corruption, and climate change, and analyzes the potential for a shift towards sustainable policies that prioritize long-term planning and environmental protection. The paper concludes by highlighting the opportunities for a more sustainable future for Pakistan and the role of political leadership in achieving this goal. Unfortunately, in a social contract between state and people of Pakistan, state has dishonored its obligation many times. The role of one of the states institution had remained over developed and to remove the label of garrison state to a welfare state, a great deal of responsibility lies with politicians and their electoral politics.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.029
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.9710.971

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 head0.011
GPT teacher head0.234
Teacher spread0.223 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

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
Published2000
Admission routes1
Has abstractyes

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