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Record W4411397213 · doi:10.53762/pck1mn59

10.53762/pck1mn59

2000· article· en· W4411397213 on OpenAlexvenueno aff
Mian Saeed Ahmad, Noor Hamid Khan Mahsud, Muhammad Naeem Khan

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicPolitics and Conflicts in Afghanistan, Pakistan, and Middle East
Canadian institutionsnot available
Fundersnot available
KeywordsOpposition (politics)PoliticsPolitical scienceAllianceIslamDictatorLawPolitical economyAuthoritarianismIdeologySociologyDemocracyHistory

Abstract

fetched live from OpenAlex

It’s a historical fact that Bhutto government introduced a number of reforms for the development of the country. However, as far as concentration of powers and prolonging his rule is concerned, he was no less than a dictator. His concentration of powers in his own person even created differences within his own party. On the other hand, the rapidly increasing inflation and law and order issues particularly the murder of some well-known personalities led to anti-Bhutto sentiments among the people. It was in these circumstances that his political opponents started a propaganda against his governance style. In the start of 1977, Bhutto announced elections before the expiry of the already serving assemblies. The opposition parties formed an electoral alliance called Pakistan National Alliance[1] (PNA). The Alliance consisted of nine parties with a diverse set of ideologies, backgrounds, and political goals. The PNA started propaganda against the governance style of Bhutto and alleged that Bhutto would rig the upcoming elections. Despite the fact that the nine political parties adhered to different socio-political values, a slogan to Islamize the political system of the country was the most common factor among them. Thus, they promised that they will enforce Islamic laws (Nizam-e-Mustafa) and Sharia if came into power. Opposition to the autocratic rule by Bhutto and his party PPP seemed to be the main force holding the otherwise diverse nine political parties together.

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)0.002
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 score0.039
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0050.003
Open science0.0020.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.9610.972

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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