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Record W4392007533 · doi:10.5406/15351882.137.543.14

Dictionary of Authentic American Proverbs

2024· article· en· W4392007533 on OpenAlexaboutno aff
Erik Aasland

Bibliographic record

VenueJournal of American Folklore · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicLexicography and Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLinguisticsArtLiteratureHistoryPhilosophy

Abstract

fetched live from OpenAlex

The Dictionary of Authentic American Proverbs is the culmination of 50 years of Wolfgang Mieder's proverb scholarship. He has published numerous works on proverbs in North America, but previous works did not draw a distinction between American (US) and British proverbs in use in North America. In the case of this dictionary, Mieder follows scholarly principles in tracking down first occurrences of proverbs that were coined in North America (and in a few cases, Canada, p. 4) from the seventeenth to the twenty-first century.The nearly 40-page introduction covers topics of the origin of proverbs in North America, loan proverbs of North American origin, obvious American (US) proverbs, structure and variants, and anti-proverbs, as well as themes and American (US) values. It is a tour de force of Mieder's proverb research acumen.With any inquiry into authenticity, the question arises about how those not meeting the cut are classified. What does it mean for the proverbs that Mieder evaluates to be found to be “inauthentic”? Are they designated as “fakelore”? No, in most cases, those that did not make the cut did so because of a different origin. As noted earlier, there are numerous proverbs of British origin in use in North America.Mieder does not dwell on the details of the scientific approaches he has taken to bring together this collection of proverbs. He started years ago with LexisNexis full-text searches and expanded into other resources, thereby taking the discipline of proverb research far beyond what Archer Taylor had envisioned in terms of proverb research excellence. The result is this superb collection, which demonstrates the wealth of proverbial riches predominantly from the United States.Even with the wealth of these proverbs, Mieder is reticent to make sweeping generalizations about an American or national character from the collection of US proverbs. For one thing, his collection of proverbs does not contain enough data to make such generalizations. Moreover, the proverbs were coined over the course of centuries, which also limits the ability to make sweeping statements. Still, Mieder does point out some of the most significant themes and tendencies from the collection.One topic I would have liked Mieder to unpack a bit more is the idea of a paremiological minimum for American proverbs, that is, the idea that a researcher may suggest a basic set of proverbs for those learning English as a foreign language to gain a degree of cultural competency. I believe it would have fit well with this proverb collection.The dictionary organizes the proverbs alphabetically by a keyword, which it indicates through the use of bold font. This may or may not be the first word in the proverb. For example: “There is no friend like a dollar” (p. 74). Each entry includes the year of first occurrence and often provides a brief explanatory note.The Dictionary of Authentic American Proverbs will be of interest to folklorists, anthropologists, linguists, and literary scholars. Language used in the preface is easily accessible for the general public, and the topic would be of interest to a broader readership. The lists are also easy to understand and should serve as a ready resource to the wealth of authentic American (US) proverbs.My own proverb research focuses on proverb use in Kazakhstan, a society with an emphasis in maintaining its rich oral traditions. In contrast, I often have conversations with fellow US citizens who find it challenging to call to mind English proverbs. Mieder's collection of 1,500 proverbs from the United States, as well as his section discussing loan proverbs from English, is a welcome corrective. I will keep this book handy to show off the wealth of proverbs from the United 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 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)0.008
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: Other · Consensus signal: Other
Teacher disagreement score0.069
Threshold uncertainty score0.232

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0070.007
Science and technology studies0.0040.004
Scholarly communication0.0070.006
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0690.030

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 head0.010
GPT teacher head0.244
Teacher spread0.233 · 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
GenreOther

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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