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References

ProtoLingua does not invent its linguistics. Every structural question in the app traces back to published fieldwork, and the percentages beside the answers are read from these datasets at run time rather than written in by hand. This page says exactly whose work that is.

Datasets

Five databases are embedded in the application. Each entry gives the licence it is published under and states what was taken, since none of them ships here whole.

Dryer, Matthew S. & Haspelmath, Martin (eds.) 2013. The World Atlas of Language Structures Online. Leipzig: Max Planck Institute for Evolutionary Anthropology.
What this app uses: A subset of features and the languages coded for them, reformatted as a compressed table. No coded value was altered.
Skirgård, Hedvig et al. 2023. Grambank v1.0.3. Leipzig: Max Planck Institute for Evolutionary Anthropology.
What this app uses: A subset of features and the languages coded for at least ten of them, reformatted as a compressed table. No coded value was altered.
Moran, Steven & McCloy, Daniel (eds.) 2019. PHOIBLE 2.0. Jena: Max Planck Institute for the Science of Human History.
What this app uses: The phoneme inventories joined into one row per inventory, with a subset of the metadata columns. No segment was altered.
List, Johann-Mattis, Forkel, Robert, Greenhill, Simon J. et al. 2022. Lexibank, a public repository of standardized wordlists with computed phonological and lexical features.
What this app uses: Cross-linguistic segment and syllable-shape frequencies only. No wordlist is reproduced.
Rzymski, Christoph, Tresoldi, Tiago et al. 2020. The Database of Cross-Linguistic Colexifications, reproducible analysis of cross-linguistic polysemies. Scientific Data 7.
What this app uses: Not reproduced. One relative word-length factor per concept, computed here from the word forms and shipped in place of the source data.

PHOIBLE asks that inventory data cite the original source corpus rather than only the aggregate. The inventories embedded here come from SPA, UPSID, AA, PH, GM, RA, SAPHON, UZ, EA and ER.

Works the app is built on

Not data, but the findings the questions are shaped around. Where the app tells you something is near-universal, this is where that claim comes from.

  • Berlin, Brent & Kay, Paul (1969). Basic Color Terms: Their Universality and Evolution. Berkeley: University of California Press. The order colour terms enter a language, which the colour questions follow and which settles the green/blue split for a language below the five-term stage.
  • Comrie, Bernard & Smith, Norval (1977). Lingua Descriptive Studies: Questionnaire. Lingua 42. The standard checklist for describing a language. Its section numbers are carried on the questions, and the Conformance page answers it from your language.
  • Greenberg, Joseph H. (1963). Some Universals of Grammar with Particular Reference to the Order of Meaningful Elements. In Universals of Language. MIT Press. The word-order correlations the typology report checks — universals 2, 4 and 24 by name.
  • Hockett, Charles F. (1960). The Origin of Speech. Scientific American 203. The design features. What makes a system a language at all, and the first questions the app asks.
  • Keenan, Edward L. & Comrie, Bernard (1977). Noun Phrase Accessibility and Universal Grammar. Linguistic Inquiry 8. The accessibility hierarchy: languages relativise an unbroken run from the top of it, which is why the app asks where your language stops rather than which positions it allows.
  • Nichols, Johanna (1986). Head-Marking and Dependent-Marking Grammar. Language 62. Where a relationship is marked — on the head or on the dependent. One of the deepest divisions between language types.
  • Zipf, George K. (1949), and Bentz, Christian & Ferrer-i-Cancho, Ramon (2016). The law of abbreviation: the things a language says most often, it says most briefly. Measured here across 1.46 million word forms rather than assumed, and applied when the app coins a word.

A note on what is measured

Where this app says a choice is rare, it means the figure was counted in one of the datasets above at the moment the page was drawn. Nothing is hard-coded, so regenerating a dataset moves the figures and cannot leave a stale number behind. Where nothing honest can be said, no figure is shown at all.