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Record W3123480455 · doi:10.11575/sppp.v12i0.56878

Two Different Conflicts in Federal Systems: An Application to Canada

2018· article· en· W3123480455 on OpenAlexaffabout
Jack Mintz

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsTasteContext (archaeology)PoliticsPolitical sciencePolitical economyPer capitaEconomicsSociologyGeographyLawPopulationPsychology

Abstract

fetched live from OpenAlex

The analysis contained in this paper focuses on two different forms of regional conflict in a federation: conflict of taste and conflict of claim. These conflicts may support each other but not necessarily – they are independent in concept and have different implications for regional tensions. Conflict of taste arises from differences in political preferences amongst populations arising from institutions, historical context and culture. Conflict of claim arises from one region having greater wealth than others and being expected to share it with others. The latter is particularly problematical when the rich region is small and has little influence in determining transfers as large per capita transfers from a small rich are needed to have any significant impact on large populated poor regions. While, both conflicts lead to regional stress and a possible break-up of a federation, conflict of claim can be divisive since it focuses on sharing the pie rather than creating the pie.

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)0.003
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.574

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.006
Science and technology studies0.0130.005
Scholarly communication0.0060.002
Open science0.0020.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.195
GPT teacher head0.552
Teacher spread0.357 · 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 designTheoretical or conceptual
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
Published2018
Admission routes2
Has abstractyes

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