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Record W7019964446

Javaslatcsomag a hazai országgyűlési választókerületi rendszer felülvizsgálatára = Proposals for the revision of the Hungarian parliamentary
\nconstituency system

2024· article· hu· W7019964446 on OpenAlexaboutno aff

Bibliographic record

VenueRepository of the Academy's Library (Library of the Hungarian Academy of Sciences) · 2024
Typearticle
Languagehu
FieldSocial Sciences
TopicHungarian Social, Economic and Educational Studies
Canadian institutionsnot available
Fundersnot available
KeywordsProportionality (law)RedistrictingProcess (computing)Executive branch
DOInot available

Abstract

fetched live from OpenAlex

A többségi választási rendszerekben a választókerületek kialakításának folyamatát állandó tudományos párbeszéd és politikai \ncsatározások egyaránt kísérik, hiszen ezek \ndöntő mértékben befolyásolni tudják a választások végkimenetelét. A nemzetközi \nszakirodalomban és joggyakorlatban különböző módszereket alkalmaznak a választókerület-határok meghatározásával kapcsolatos vitás kérdések rendezésére. Magyarországon azonban a törvényhozás részéről \nnincs arra kialakított módszertan, hogy az \nesetlegesen aránytalanná váló térfelosztást \nmikor és milyen alapelvek mentén vizsgálják \nfelül. Már a 2011-ben elvégzett új választókerületi besorolást sem előzte meg semmilyen szakmai vagy társadalmi egyeztetés. Az \nEgyesült Államok, az Egyesült Királyság és \nKanada gyakorlatának tanulmányozásával a \nszerzők kialakítottak egy eljárásrendet, amely \nmentén felülvizsgálhatók a kerülethatárok, \ntovábbá egy javaslatcsomagot a választókerületek vármegyék közötti elosztásának módosítására, valamint a módosított kerületszámmal rendelkező vármegyékben lévő új \nkerületek határaira. Az eredmények azt mutatják, hogy a javasolt rendszer hosszú távon \n(minimum 10 évre előrevetítve) – a népességszám aránytalanságának minimálisra szorításával – fenntartható. | Redistricting is constantly accompanied by \npolitical conflicts as well as academic arguments in countries with majoritarian or mixed electoral system, as a result of the process could potentially influence the outcome \nof elections. In the international scientific \ndiscourse and legal processes, this conflict is \nmanaged by different approaches. So far, Hungary didn’t implement such methodologies by the executive branches, therefore \nsuch anomalies as malapportionment, are \nnot taken care of, as the electoral reform of \n2011 has not been advanced by any kind of \nsocial or scientific disputes. Having reviewed \nexisting processes of redistricting in the US, \nUK, and Canada, a procedure was created \nin this paper for revising district boundaries, that would fulfill the requirement of proportionality in respect of Hungary as well. \nTo achieve that, at the first place, proportionality among counties must be assured. \nSecondly, if a given county will have modified number of constituencies, district borders \nmust be redrawn to gain proportional representation of voters. The results show, that \nthe proposed subdivision would provide \nproportional allocation for the forthcoming \n10 years at least.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.055
Threshold uncertainty score0.183

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0100.002
Open science0.0010.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0550.018

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 head0.029
GPT teacher head0.281
Teacher spread0.252 · 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 designNot applicable
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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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