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Record W257951498

Joining the Great Plains in Space, Place, and Time: Questioning a Time Zone Boundary.

2011· article· en· W257951498 on OpenAlexaboutno aff
Rob Kuper

Bibliographic record

VenueLincoln (University of Nebraska) · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicDiverse Educational Innovations Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTime zoneBoundary (topology)SpacetimeTime spaceSpace timeGeographyHistoryMathematicsLinguisticsEngineeringPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Standard time zone boundaries are invisible in the landscape, yet they abruptly delineate a temporal difference of one hour between two large areas located relative to one another on Earth. In most cases, standard time zone boundaries follow political ones and define areas within which daylight saving time (DST)-the seasonal advancement of standard time by one hour-is observed. Moving time zone boundaries and the decision to observe daylight saving time occurs throughout the world for various reasons that result in the synchronization of socioeconomic and political activities within and between communities and the simultaneous separation from others. The zone boundary between mountain standard time (MST) and central standard time (CST) in the Great Plains of the United States now follows the mostly rectilinear political boundaries of counties and states from the Canadian border in the north t'o the Mexican border in the south. North and South Dakota, Nebraska, Kansas, and Texas are bisected by the standard time zone boundary. All Plains states observe DST. Two consequences result from this current configuration: first, communities on either side of the MST-CST zone boundary are united by time but may not be related by environmental characteristics; and second, that observing or eliininating DST in one state depends upon observance or elimination in neighboring states.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.362
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.024
GPT teacher head0.185
Teacher spread0.161 · 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.

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

Citations1
Published2011
Admission routes1
Has abstractyes

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