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Record W4386576223 · doi:10.47205/jdss.2022(3-1)18

Building Bridges and Shaping Policies: A Comparative Study of Organizational Structures and Policy Implementation in the Pakistan People's Party and Liberal Party of Canada (1971-1978)

2023· article· en· W4386576223 on OpenAlexaboutno aff
Qadeer Hussain

Bibliographic record

VenueJournal of Development and Social Sciences · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicPolitics and Conflicts in Afghanistan, Pakistan, and Middle East
Canadian institutionsnot available
Fundersnot available
KeywordsOrganizational structurePublic relationsPolitical scienceOrganizational studiesPublic administrationOrganizational theoryComparative caseSociologyOrganization developmentEconomicsManagementLaw

Abstract

fetched live from OpenAlex

This research examines the organizational structures and policy implementation approaches of the Pakistan People's Party (PPP) and the Liberal Party of Canada (LPC) during the period of 1971-1978. By applying Institutional Theory, the study explores how institutional factors shape organizational behavior, influence party dynamics, and impact policy implementation. The research highlights the importance of considering both formal and informal rules, norms, and structures in understanding organizational structures and their implications for policy implementation outcomes. Through a comparative analysis, the study identifies similarities and differences between the PPP and LPC, considering their organizational structures, policy implementation approaches, hierarchical divide, and decision-making processes. The findings emphasize the significance of institutional contexts, historical landscapes, and leadership dynamics in shaping party behavior and policy outcomes. This research contributes to a deeper understanding of organizational structures, policy implementation, and the interplay between institutions and party behavior.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.427
Threshold uncertainty score0.951

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.071
GPT teacher head0.398
Teacher spread0.327 · 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 designObservational
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
Published2023
Admission routes1
Has abstractyes

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