---
title: "Gendered associations of English morphology (2018)"
description: "The paper asks whether social-indexical information, specifically speaker gender, attaches to English… 35 references, cited by 4 papers here."
authors: ["Janet Pierrehumbert", "Jeremy Michael Needle"]
year: 2018
venue: "Laboratory Phonology 9"
source: "https://www.journal-labphon.org/article/id/6231/"
doi: "10.5334/labphon.134"
licence: "CC BY (journal licence per DOAJ; Laboratory Phonology)"
licence_url: "https://creativecommons.org/licenses/by/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/pierrehumbert-2018-gendered-associations-english-morphology/"
---
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# Gendered associations of English morphology

**Authors:** [Janet Pierrehumbert](https://md.research.elamur.ai/free/en/authors/janet-pierrehumbert/) and Jeremy Michael Needle · **Year:** 2018 · **Venue:** [Laboratory Phonology 9](https://md.research.elamur.ai/free/en/venues/laboratory-phonology-journal-of-the-association-for-laboratory-phonology/) ([Laboratory Phonology Journal of the Association for Laboratory Phonology 2018](https://md.research.elamur.ai/free/en/venues/laboratory-phonology-journal-of-the-association-for-laboratory-phonology/2018/)) · **Publisher:** [Ubiquity Press](https://md.research.elamur.ai/free/en/publishers/ubiquity-press/) · **Licence:** [CC BY (journal licence per DOAJ; Laboratory Phonology)](https://creativecommons.org/licenses/by/4.0/)

**Links:** [Publisher's page](https://doi.org/10.5334/labphon.134) · [PDF](https://www.journal-labphon.org/article/id/6231/download/pdf/) · [DOI 10.5334/labphon.134](https://doi.org/10.5334/labphon.134) · [OpenAlex](https://openalex.org/W2890859887)

**Citations:** 16 citations (OpenAlex, 2026-10-14) · [4](https://md.research.elamur.ai/free/en/papers/pierrehumbert-2018-gendered-associations-english-morphology/cited-by/) in our library, of the 141,840 papers whose bibliographies we read

## Summary
The paper asks whether social-indexical information, specifically speaker gender, attaches to English derivational morphemes and compounding elements as well as to whole words and sounds. The authors first used corpus statistics to find words and morphemes whose usage differs between men and women. They then built stimuli that were male-biased, female-biased or neutral. These included real simple words, real complex words, and pseudowords such as thrafium and pelpcase, formed by suffixation or compounding. Participants guessed the likely gender of the speaker for each item and, in the same protocol, judged whether the item splits into parts. People matched real words to the corpus gender bias above chance. For pseudowords, their guesses followed the bias of the component morphemes. However, this transfer did not depend on whether participants explicitly decomposed the item, or on cues for decomposition. For real words, knowledge of the whole word overrode the parts. The authors read this as evidence for a general analogical mechanism, close to NDL, rather than rule-based parsing that carries social meaning.

## Key points
- Gender bias of stimuli was taken from corpus usage counts. Items were crossed by lexicality (real vs. pseudoword), complexity (simple vs. complex), structure (compound vs. suffixation), morpheme bias and whole-word bias.
- Gender guesses for pseudowords tracked the morpheme bias. They were unrelated to explicit decomposition judgments and to the orthographic boundary cue.
- For real words, responses reflected mainly the whole-word bias. Unexpectedly, the whole-word bias was stronger for words containing more woman-biased morphemes, which the authors attribute to register or attention.
- Several lexicon models were compared (multiple-route, Albright & Hayes-style rules, NDL of Baayen et al. 2013). Whatever the model, it must let whole-word knowledge take priority over composition.
- The full stimulus list is released as a tab-delimited appendix (s1-labphon-134_needle.txt), with columns for morpheme group, lexicality, structure, gender categories and boundary ratio.

## Interesting ideas
- Running an explicit decomposition task alongside the target judgment shows whether an effect actually passes through parsing or bypasses it.
- Pseudowords built from real morphemes isolate what the parts contribute when no whole-word knowledge exists.
- Whole-word knowledge supersedes compositional analysis whenever it is available, the same priority that keeps irregular forms like "kept" stable.
- Associations of a word can be indirect, carried through register or topic rather than direct meaning (higher-order indexicality).
- Stimulus metadata was crossed factorially and released as a plain table, so the design can be reproduced and controlled.

## For Mova

How these ideas could serve Mova, our small open language model — its files, stages and tests:

- **I1** (learn): Probing model decisions with paired "did you segment this?" diagnostics would show whether a morphology-based feature truly drives the decision, which works as a negative control.
- **I2** (tokens): Nonce words like "thrafium" could serve as test items to check that the en crate's affix analysis generalizes and produces sensible lemma and POS guesses for unseen forms.
- **I3** (tokens): Lexicon lookup should strictly override rule-based morphological analysis, with rules used only as a fallback for unknown words, and every override logged for explainability.
- **I4** (frames): Pragmatic inference about speaker or register should keep the mediating link explicit (e.g., word → casual register → inferred trait) instead of jumping straight to a conclusion.
- **I5** (learn): Evaluation sets could be built as factorial tables (known/novel × simple/complex × structure) so that error analysis can pinpoint which factor breaks the system.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

## Institutions

- [University of Oxford](https://md.research.elamur.ai/free/en/universities/university-of-oxford/) — University, Oxford, United Kingdom · 52 works · 154,829 citations
- [Northwestern University](https://md.research.elamur.ai/free/en/universities/northwestern-university/) — University, Evanston, United States · 12 works · 1,971 citations

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🧭 Topics (2): [English](https://md.research.elamur.ai/free/en/topics/english/) · 1,373 works · [🧩 Morphology](https://md.research.elamur.ai/free/en/topics/morphology/) · 277 works

## Cite

Cite as: Janet Pierrehumbert and Jeremy Michael Needle. 2018. Gendered associations of English morphology. Laboratory Phonology 9.

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@inproceedings{pierrehumbert2018gendered,
  title = {{Gendered associations of English morphology}},
  author = {Janet Pierrehumbert and Jeremy Michael Needle},
  booktitle = {Laboratory Phonology 9},
  year = {2018},
  doi = {10.5334/labphon.134},
  url = {https://doi.org/10.5334/labphon.134}
}
```

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## References

35 references, 2 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

1. Albright, A., & Hayes, B. 2003. Rules vs. analogy in English past tenses: A computational/experimental study. Cognition, 90(2), 119–161. DOI: https://doi. org/10.1016/S0010-0277(03)00146-X Baayen, R. H., Hendrix, P., & Ramscar, M. 2013. Sidestepping the combinatorial explosion: An explanation of n-gram frequency effects based on naive discriminative learning. Language and Speech, 56(3), 329–347. DOI: https://doi.org/10.1177/0023 830913484896 Baayen, R. H., Piepenbrock, R., & Gulikers, L. 1995. The CELEX Lexical Database (Release 2). Philadelphia, PA: Linguistic Data Consortium, University of Pennsylvania. [↗](https://doi.org/10.1016/s0010-0277(03)00146-x)
2. Bates, D., Maechler, M., Bolker, B., & Walker, S. 2015. [Fitting linear mixed-effects models using lme4](https://md.research.elamur.ai/free/en/papers/bates-2015-fitting-linear-mixed-effects-models/). Journal of Statistical Software, 67(1), 1–48. DOI: https://doi.org/10.18637/ jss.v067.i01 Bauer, L. 2001. Morphological productivity. Cambridge University Press. DOI: https://doi. org/10.1017/CBO9780511486210 Beckner, C., Rácz, P., Hay, J., Brandstetter, J., & Bartneck, C. 2016. Participants conform to humans but not to humanoid robots in an English past tense formation task. Journal of Language and Social Psychology, 35(2), 158–179. DOI: https://doi. org/10.1177/0261927X15584682 Boulis, C., & Ostendorf, M. 2005. Text classification by augmenting the bag-of-words representation with redundancy compensated bigrams. In: Proceedings of the International Workshop in Feature Selection in Data Mining, 9–16. [↗](https://doi.org/10.1017/cbo9780511486210)
3. Bucholtz, M. 1999. “Why be normal?”: Language and identity practices in a community of nerd girls. Language in Society, 28(2), 203–223. DOI: https://doi.org/10.1017/ S0047404599002043 Bucholtz, M. 2001. The whiteness of nerds: Superstandard English and racial markedness. Journal of Linguistic Anthropology, 11(1), 84–100. DOI: https://doi.org/10.1525/ jlin.2001.11.1.84 Bybee, J. 1995. Regular morphology and the lexicon. Language and Cognitive Processes, 10(5), 425–455. DOI: https://doi.org/10.1080/01690969508407111 [↗](https://doi.org/10.1080/01690969508407111)
4. Bybee, J., & Thompson, S. 1997. Three frequency effects in syntax. In: Annual Meeting of the Berkeley Linguistics Society, 23(1), 378–388. DOI: https://doi.org/10.3765/bls. v23i1.1293 Clopper, C. G., & Pisoni, D. B. 2004a. Homebodies and army brats: Some effects of early linguistic experience and residential history on dialect categorization. Language Variation and Change, 16(1), 31–48. DOI: https://doi.org/10.1017/S0954394504161036 [↗](https://doi.org/10.3765/bls)
5. Clopper, C. G., & Pisoni, D. B. 2004b. Some acoustic cues for the perceptual categorization of American English regional dialects. Journal of Phonetics, 32(1), 111–140. DOI: https://doi.org/10.1016/S0095-4470(03)00009-3 [↗](https://doi.org/10.1016/s0095-4470(03)00009-3)
6. Clopper, C. G., Tamati, T. N., & Pierrehumbert, J. B. 2016. Variation in the strength of lexical encoding across dialects. Journal of Phonetics, 58, 87–103. DOI: https://doi.org/10.1016/j.wocn.2016.06.002 Daelemans, W., Zavrel, J., Van der Sloot, K., & Van den Bosch, A. 2010. TiMBL: Tilburg Memory Based Learner, version 6.3, Reference Guide. ILK Research Group Technical Report Series no. 10-01. [↗](https://doi.org/10.1016/j.wocn.2016.06.002)
7. Daland, R., & Pierrehumbert, J. B. 2011. Learning diphone‐based segmentation. Cognitive Science, 35(1), 119–155. DOI: https://doi.org/10.1111/j.1551-6709.2010.01160.x [↗](https://doi.org/10.1111/j.1551-6709.2010.01160.x)
8. Daland, R., Sims, A. D., & Pierrehumbert, J. 2007, June. Much ado about nothing: A social network model of Russian paradigmatic gaps. In: Annual Meeting – Association for Computational Linguistics, 45(1), 936. [find](https://scholar.google.com/scholar?q=Daland%2C+R%2E%2C+Sims%2C+A%2E+D%2E%2C+%26+Pierrehumbert%2C+J%2E+2007%2C+June%2E+Much+ado+about+nothing%3A+A+social+network+model+of+Russian+paradigmatic+gaps%2E+In%3A+Annual+Meeting+%E2%80%93+Association+for+Computational+Linguistics%2C+45)
9. Dawdy-Hesterberg, L. G., & Pierrehumbert, J. B. 2014. Learnability and generalisation of Arabic broken plural nouns. Language, Cognition and Neuroscience, 29(10), 1268–1282. DOI: https://doi.org/10.1080/23273798.2014.899377 [↗](https://doi.org/10.1080/23273798.2014.899377)
10. Eckert, P. 1989. The whole woman: Sex and gender differences in variation. Language Variation and Change, 1(3), 245–267. DOI: https://doi.org/10.1017/ S095439450000017X Eckert, P. 2008. Variation and the indexical field. Journal of Sociolinguistics, 12(4), 453– 476. DOI: https://doi.org/10.1111/j.1467-9841.2008.00374.x [↗](https://doi.org/10.1111/j.1467-9841.2008.00374.x)
11. Foulkes, P., & Docherty, G. 2006. The social life of phonetics and phonology. Journal of Phonetics, 34(4), 409–438. DOI: https://doi.org/10.1016/j.wocn.2005.08.002 [↗](https://doi.org/10.1016/j.wocn.2005.08.002)
12. German, J. S., Carlson, K., & Pierrehumbert, J. B. 2013. Reassignment of consonant allophones in rapid dialect acquisition. Journal of Phonetics, 41(3), 228–248. DOI: https://doi.org/10.1016/j.wocn.2013.03.001 [↗](https://doi.org/10.1016/j.wocn.2013.03.001)
13. Haspelmath, M., & Sims, A. 2013. Understanding morphology (2nd ed.). Routledge, Taylor Francis Group. London. [find](https://scholar.google.com/scholar?q=Haspelmath%2C+M%2E%2C+%26+Sims%2C+A%2E+2013%2E+Understanding+morphology+%282nd+ed%2E%29%2E+Routledge%2C+Taylor+Francis+Group%2E+London%2E)
14. Hay, J. 2002. From speech perception to morphology: Affix ordering revisited. Language, 78(3), 527–555. DOI: https://doi.org/10.1353/lan.2002.0159 [↗](https://doi.org/10.1353/lan.2002.0159)
15. Hay, J., & Baayen, H. 2001. Parsing and productivity. In: Yearbook of Morphology 2001, 203–235. Springer: Netherlands. [↗](https://doi.org/10.1007/978-94-017-3726-5_8)
16. Hay, J., & Drager, K. 2010. Stuffed toys and speech perception. Linguistics, 48(4), 865– 892. DOI: https://doi.org/10.1515/ling.2010.027 [↗](https://doi.org/10.1515/ling.2010.027)
17. Hay, J., Pierrehumbert, J., & Beckman, M. 2004. Speech perception, well-formedness, and the statistics of the lexicon. Papers in Laboratory Phonology VI, 58–74. [find](https://scholar.google.com/scholar?q=Hay%2C+J%2E%2C+Pierrehumbert%2C+J%2E%2C+%26+Beckman%2C+M%2E+2004%2E+Speech+perception%2C+well%2Dformedness%2C+and+the+statistics+of+the+lexicon%2E+Papers+in+Laboratory+Phonology+VI%2C+58%E2%80%9374%2E)
18. Hay, J., Warren, P., & Drager, K. 2006. Factors influencing speech perception in the context of a merger-in-progress. Journal of Phonetics, 34(4), 458–484. DOI: https://doi.org/10.1016/j.wocn.2005.10.001 Hay, J. B., & Baayen, R. H. 2005. Shifting paradigms: gradient structure in morphology. Trends in Cognitive Sciences, 9(7), 342–348. DOI: https://doi.org/10.1016/j. tics.2005.04.002 Johnson, K. 2006. Resonance in an exemplar-based lexicon: The emergence of social identity and phonology. Journal of Phonetics, 34(4), 485–499. DOI: https://doi. org/10.1016/j.wocn.2005.08.004 Komarova, N. L., & Nowak, M. A. 2001. The evolutionary dynamics of the lexical matrix. Bulletin of Mathematical Biology, 63(3), 451–484. DOI: https://doi.org/10.1006/ bulm.2000.0222 Kuperman, V. 2013. Accentuate the positive: Semantic access in English compounds. Frontiers in Psychology, 4, 203. DOI: https://doi.org/10.3389/fpsyg.2013.00203 [↗](https://doi.org/10.1016/j.wocn.2005.10.001)
19. Labov, W. 2001. Principles of linguistic change. Social factors, 2. Oxford, UK: Blackwell. [find](https://scholar.google.com/scholar?q=Labov%2C+W%2E+2001%2E+Principles+of+linguistic+change%2E+Social+factors%2C+2%2E+Oxford%2C+UK%3A+Blackwell%2E)
20. Lakoff, R. 1973. Language and woman’s place. Language in Society, 2(1), 45–79. DOI: https://doi.org/10.1017/S0047404500000051 [↗](https://doi.org/10.1017/s0047404500000051)
21. Mihalcea, R., & Garimella, A. 2016. What men say, what women hear: Finding gender-specific meaning shades. IEEE Intelligent Systems, 31(4), 62–67. DOI: https://doi.org/10.1109/MIS.2016.71 Nation, K., & Cocksey, J. 2009. Beginning readers activate semantics from subword orthography. Cognition, 110(2), 273–278. DOI: https://doi.org/10.1016/j. cognition.2008.11.004 Needle, J. M., Pierrehumbert, J. B., & Hay, J. B. under review. Phonotactic and morphological effects in the acceptability of pseudowords. [↗](https://doi.org/10.1109/mis.2016.71)
22. Nevalainen, T., Raumolin-Brunberg, H., & Mannila, H. 2011. The diffusion of language change in real time: Progressive and conservative individuals and the time depth of change. Language Variation and Change, 23(1), 1–43. DOI: https://doi.org/10.1017/ S0954394510000207 Nosofsky, R. M. 1988. Similarity, frequency, and category representations. Journal of Experimental Psychology: Learning, Memory, and Cognition, 14(1), 54–65. DOI: https://doi.org/10.1037/0278-7393.14.4.700 Nosofsky, R. M. 1990. Relations between exemplar-similarity and likelihood models of classification. Journal of Mathematical Psychology, 34(4), 393–418. DOI: https://doi. org/10.1016/0022-2496(90)90020-A Ochs, E. 1992. Indexing gender. In: Rethinking context: Language as an interactive phenomenon, 11, 335. [↗](https://doi.org/10.1037/0278-7393.14.4.700)
23. Pierrehumbert, J. B. 2006. The next toolkit. Journal of Phonetics, 34(4), 516–530. DOI: https://doi.org/10.1016/j.wocn.2006.06.003 [↗](https://doi.org/10.1016/j.wocn.2006.06.003)
24. Pierrehumbert, J. B. 2016. Phonological representation: Beyond abstract versus episodic. Annual Review of Linguistics, 2, 33–52. DOI: https://doi.org/10.1146/annurev-linguistics-030514-125050 [↗](https://doi.org/10.1146/annurev-linguistics-030514-125050)
25. Plag, I., Dalton-Puffer, C., & Baayen, H. 1999. Morphological productivity across speech and writing. English Language & Linguistics, 3(2), 209–228. DOI: https://doi.org/10.1017/ S1360674399000222 Purnell, T., Idsardi, W., & Baugh, J. 1999. Perceptual and phonetic experiments on American English dialect identification. Journal of Language and Social Psychology, 18(1), 10–30. DOI: https://doi.org/10.1177/0261927X99018001002 [↗](https://doi.org/10.1177/0261927x99018001002)
26. Quina, K., Wingard, J. A., & Bates, H. G. 1987. Language style and gender stereotypes in person perception. Psychology of Women Quarterly, 11(1), 111–122. DOI: https://doi.org/10.1111/j.1471-6402.1987.tb00778.x Rácz, P., Hay, J. B., & Pierrehumbert, J. B. 2017. Social Salience Discriminates Learnability of Contextual Cues in an Artificial Language. Frontiers in Psychology, 8. DOI: https://doi.org/10.3389/fpsyg.2017.00051 Rácz, P., Pierrehumbert, J. B., Hay, J. B., & Papp, V. 2015. Morphological emergence. The Handbook of Language Emergence, 123–146. DOI: https://doi. org/10.1002/9781118346136.ch5 R Core Team. 2014. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Available from: http://www.R-project.org/. [↗](https://doi.org/10.1111/j.1471-6402.1987.tb00778.x)
27. Rickford, J. R., & Rickford, R. J. 2000. Spoken Soul: The Story of Black English. John Wiley and Sons. [find](https://scholar.google.com/scholar?q=Rickford%2C+J%2E+R%2E%2C+%26+Rickford%2C+R%2E+J%2E+2000%2E+Spoken+Soul%3A+The+Story+of+Black+English%2E+John+Wiley+and+Sons%2E)
28. Silverstein, M. 2003. Indexical order and the dialectics of sociolinguistic life. Language & Communication, 23(3–4), 193–229. DOI: https://doi.org/10.1016/S0271-5309(03)00013-2 [↗](https://doi.org/10.1016/s0271-5309(03)00013-2)
29. Social Security Administration. 2016, May 5. Top Names Over the Last 100 Years. Retrieved from: [https://www.ssa.gov/OACT/babynames/decades/century.html](https://www.ssa.gov/OACT/babynames/decades/century.html). [↗](https://www.ssa.gov/OACT/babynames/decades/century.html)
30. Sumner, M., & Samuel, A. G. 2009. The effect of experience on the perception and representation of dialect variants. Journal of Memory and Language, 60(4), 487–501. DOI: https://doi.org/10.1016/j.jml.2009.01.001 [↗](https://doi.org/10.1016/j.jml.2009.01.001)
31. Taft, M. 2004. Morphological decomposition and the reverse base frequency effect. Quarterly Journal of Experimental Psychology, 57A(4), 745–765. DOI: https://doi.org/10.1080/02724980343000477 The British National Corpus, Version 3 (BNC XML Edition). 2007. Distributed by Bodleian Libraries, University of Oxford, on behalf of the BNC Consortium. URL: http://www. natcorp.ox.ac.uk/. [↗](https://doi.org/10.1080/02724980343000477)
32. How to cite this article: Needle, J. M. and Pierrehumbert, J. B. 2018 [Gendered associations of English morphology](https://md.research.elamur.ai/free/en/papers/pierrehumbert-2018-gendered-associations-english-morphology/). Laboratory Phonology: Journal of the Association for Laboratory Phonology 9(1): 14, pp. 1–23, DOI: https://doi.org/10.5334/labphon.134 [↗](https://doi.org/10.5334/labphon.134)
33. Submitted: 12 January 2018 [find](https://scholar.google.com/scholar?q=Submitted%3A+12+January+2018)
34. Published: 05 September 2018 [find](https://scholar.google.com/scholar?q=Published%3A+05+September+2018)
35. Copyright: © 2018 The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See [http://creativecommons.org/licenses/by/4.0/](http://creativecommons.org/licenses/by/4.0/). Laboratory Phonology: Journal of the Association for Laboratory Phonology is a peer-reviewed open access journal published by Ubiquity Press. OPEN ACCESS [↗](http://creativecommons.org/licenses/by/4.0/)

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