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Record W2022553262 · doi:10.1353/sgo.2007.0014

Research on the Political Geography of the South, 1980-2005

2007· article· en· W2022553262 on OpenAlexaboutno aff
Gerald R. Webster, Jerrod Bowman, Daniel McGowin, H. Robinson

Bibliographic record

VenueSoutheastern geographer · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicGeographic Information Systems Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsQuarter (Canadian coin)Political geographyDemocracyWork (physics)GeographyPolitical scienceHuman geographyPolitical economyEconomic geographySociologyArchaeologyLawEngineering

Abstract

fetched live from OpenAlex

The American South has undergone tremendous change in the past quarter century. No where is this change more apparent than on the region's political landscape. Today minority voters are participating at all levels in the South's political processes. The region has also continued its movement from the Democratic to Republican parties. Have these changes received adequate attention in the political geography literature? This paper attempts to identify all articles, book chapters and books on the political geography of the South published in the past quarter century. It finds that there has been a significant increase in the rate of published work on the region's changing political landscape, and that these efforts have appeared in a wide array of outlets. The paper concludes by identifying areas in which additional work would be helpful to fully understanding the South's political landscape.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.190
Threshold uncertainty score0.377

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.008
Science and technology studies0.0030.002
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.060
GPT teacher head0.354
Teacher spread0.294 · 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 designQualitative
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

Citations9
Published2007
Admission routes1
Has abstractyes

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