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Record W4415706880 · doi:10.60087/jissr.v2i1.332

Understanding Political Economy: The Global Challenges, From Media – To Immigration

2025· article· W4415706880 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Interdisciplinary Social Sciences Review ISSN 3078-8358 · 2025
Typearticle
Language
FieldSocial Sciences
TopicGlobalization and political ideologies
Canadian institutionsUniversity Canada West
Fundersnot available
KeywordsPoliticsRelevance (law)ImmigrationInternational political economyGlobal politicsPolitical economy of climate changeMultidisciplinary approach

Abstract

fetched live from OpenAlex

This paper offers a comprehensive exploration of political economy as a multidisciplinary field that investigates the reciprocal relationship between economic systems and political structures. Drawing from economics, political science, sociology, and history, it highlights how political institutions and decisions shape economic outcomes—and vice versa—across national and global contexts. The study distinguishes political economy from conventional economics by emphasizing issues of power, equity, and governance, rather than market efficiency alone. Through critical analysis of media influence, social media dynamics, and immigration policy, the paper demonstrates how political economy provides essential insights into contemporary global challenges. By revisiting classical foundations and integrating modern case studies, it argues for the continued relevance of political economy in understanding systemic patterns and shaping informed policy responses in an increasingly interconnected world

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.

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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.949
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0030.004
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0000.001
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 head0.187
GPT teacher head0.449
Teacher spread0.262 · 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