The DOI matches its Crossref record; 62 of the 62 references it cites were found in a registry or an index.
Child-Directed Speech Is Infrequent in a Forager-Farmer Population: A Time Allocation Study
Open accessAbstract
This article provides an estimation of how frequently, and from whom, children aged 0–11 years (Ns between 9 and 24) receive one-on-one verbal input among Tsimane forager-horticulturalists of lowland Bolivia. Analyses of systematic daytime behavioral observations reveal < 1 min per daylight hour is spent talking to children younger than 4 years of age, which is 4 times less than estimates for others present at the same time and place. Adults provide a majority of the input at 0–3 years of age but not afterward. When integrated with previous work, these results reveal large cross-cultural variation in the linguistic experiences provided to young children. Consideration of more diverse human populations is necessary to build generalizable theories of language acquisition.
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“In addition, caregivers from different cultures may not all be equally talkative to their infants (see Cristia et al., 2019) which could also influence their response rates to infants' prelinguistic behaviors.”
From The role of dyadic combinations of infants' behaviors and caregivers' verbal and multimodal responses in predicting vocabulary outcomes (2025) · cites this paper as Cristia et al., 2019
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Cited by
Early Language Experience in a Tseltal Mayan Village
Casillas, M., Brown, P., & Levinson, S. C. (2020) · Child Development · doi:10.1111/cdev.13349 · Cited by 253
How Can We Accelerate Progress Towards Human-like Linguistic Generalization?
Linzen, T. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics · doi:10.18653/v1/2020.acl-main.465 · Cited by 148
What Artificial Neural Networks Can Tell Us about Human Language Acquisition
Warstadt, A., & Bowman, S. R. (2022) · Algebraic Structures in Natural Language · doi:10.1201/9781003205388-2 · Cited by 111
Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora
Warstadt, A., Mueller, A., Choshen, L., Wilcox, E., Zhuang, C., Ciro, J., Mosquera, R., Paranjabe, B., Williams, A., Linzen, T., et al. (2023) · Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning · doi:10.18653/v1/2023.conll-babylm.1 · Cited by 74
“This amount can vary by a factor of 10 or more across cultures and socio-economic groups (Cristia et al., 2019).”
Toward a comparative approach to language acquisition
Christiansen, M. H., Contreras Kallens, P., & Trecca, F. (2022) · Current Directions in Psychological Science · doi:10.1177/09637214211049229 · Cited by 41
Bigger is not always better: The importance of human-scale language modeling for psycholinguistics
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van der Klis, A., Junge, C., Adriaans, F., & Kager, R. (2025) · Infancy · doi:10.1111/infa.12626 · Cited by 5
“In addition, caregivers from different cultures may not all be equally talkative to their infants (see Cristia et al., 2019) which could also influence their response rates to infants' prelinguistic behaviors.”
Metadata
- Authors
- Cristia, A., Dupoux, E., Gurven, M., & Stieglitz, J.
- Venue
- Child Development
- Publisher
- Oxford University Press (OUP)
- Published
- 2019-04-30
- Volume
- 90
- Issue
- 3
- Pages
- 759-773
- ISSN
- 0009-3920 (ISSN-L)
- 1467-8624
- OpenAlex
- W2765364385
- Cited by
- 284
- References
- 62
- FWCI
- 44.48
- Type
- journal article
- Language
- en
- Open access
- green
- Licence
- Funders
- National Institutes of Health/National Institute on Aging (R01AG024119)
- Agence Nationale de la Recherche (ANR-14-CE30-0003 MechELex, ANR-10-IDEX-0001-02 PSL*, ANR-10-LABX-0087 IEC, ANR-2010-BLAN-1901-1 BOOTLANG, ANR‐14‐CE30‐0003 MechELex, ANR‐10‐IDEX‐0001‐02 PSL*, ANR‐10‐LABX‐0087 IEC, ANR‐2010‐BLAN‐1901‐1 BOOTLANG)
- European Research Council (E-2011-AdG 295810 BOOTPHON))
- Fondation de France
- National Science Foundation (BCS-0136274, BCS-0422690, BCS‐0136274, BCS‐0422690)
- ANR Labex IAST
- National Institutes of Health (R01AG024119)
- H2020 European Research Council (E‐2011‐AdG 295810 BOOTPHON))
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
