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Record W4412607288 · doi:10.17161/ygas.vi.24241

Pennsylvania Dutch

2025· article· en· W4412607288 on OpenAlexaboutno aff
Mark L. Louden

Bibliographic record

VenueYearbook of German-American Studies · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicLinguistics and language evolution
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Historical and sociolinguistic backgroundThe roots of the language known by its speakers as Deitsch, in English either Pennsylvania Dutch or Pennsylvania German, extend back to 18th-century Pennsylvania.Between 1710 and 1770, some 81,000 German-speaking migrants from mainly the Palatinate and adjacent regions in southwestern Germany, as well as smaller numbers from Alsace and Switzerland, arrived in America through the port of Philadelphia (Wokeck 1999).Most were farmers and craftspeople who settled in rural southeastern and south-central Pennsylvania, an area that still today is known as the Pennsylvania Dutch Country.Already by 1800, Pennsylvania Dutch-speakers began forming secondary settlements in western Pennsylvania (e.g., Somerset County) and further west, especially Ohio, and north into Southern Ontario in what was then known as Upper Canada.Other Pennsylvania Dutch speakers migrated southward along the eastern edge of the Appalachian Mountains establishing communities in Maryland, Virginia, and North Carolina.Precise information on exactly where the original German-speaking immigrants to colonial Pennsylvania originated is lacking, but on the basis of passenger lists for the ships on which they traveled we have a good sense of approximately how many people came and in which years thanks to a 1999 study by the historian Marianne Wokeck.According to Wokeck (1999: 144-46), approximately two-thirds of the Pennsylvania Dutch founder population arrived in Pennsylvania before 1755, with a peak occurring between 1749 and 1755.After 1755, migration from German-speaking Europe declined dramatically and all but ceased with the onset of the American Revolution.Although in many cases we do not know the specific communities in Central Europe from which German-speaking migrants to colonial 'we marry'; Meil [mɛ:ɬ] 'mile'.Conversely, in Midwestern Pennsylvania Dutch [aɪ] is retained before unstressed central [ə, ɐ], e.g., mir heiere [mi:ɐ haɪəɾə] 'we marry'; ich heier [ʔɪç haɪɐ] 'I marry' (Louden 1997: 81).The difference between [aɪ] and [ɛ:] is the most salient shibboleth between Lancaster and Midwestern varieties; see Keiser 2012: 75-115 for an extensive sociolinguistic analysis of this phenomenon.A third diphthong, [aʊ], is documented in older varieties of Pennsylvania Dutch, for example, in Albert F. Buffington's 1937 doctoral dissertation, which was based on data from nonsectarian speakers from Pennsylvania.Examples cited by Buffington (1937:109) include native vocabulary, e.g., Haus [haʊs], Gaul [gaʊl], laut [laʊt], as well as English borrowings, e.g., ebaut [əbaʊt] 'about', ennihau [ɛnɪhaʊ] 'anyhow', and Kraud [kɾaʊt] 'crowd'.Other studies from the same era, namely the dissertations of Alfred L. Shoemaker (1940) andJ. William Frey (1941), describe a vowel intermediate between [aʊ] and the modern long monophthong [a:] that they still identify as a diphthong.Shoemaker was a native speaker of the nonsectarian variety spoken in Lehigh County, PA, located in the northeastern region of the traditional Pennsylvania Dutch Country, who studied the Midwestern speech of Amish in Arthur, IL.Frey spoke and studied the Pennsylvania Dutch variety of eastern York County in the southwestern Dutch Country.Shoemaker (1940:14-15) describes the Arthur Amish pronunciations of Haus, Gaul, and other words with historical [aʊ] as long monophthongs followed by a "slurred vowel" (schwa): [a:ə].In a section comparing lexical differences between Arthur Amish Pennsylvania Dutch and his native variety, Shoemaker includes Lehigh pronunciations that also include [a:ə] in words that once were pronounced with [aʊ].e.g., versaue

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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)0.000
metaresearch head score (Gemma)0.001
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 score0.156
Threshold uncertainty score0.523

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.1560.036

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 head0.320
Teacher spread0.296 · 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
Published2025
Admission routes1
Has abstractyes

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Same venueYearbook of German-American StudiesSame topicLinguistics and language evolutionFrench-language works237,207