| Title |
Conceptual precursors to language
|
|---|---|
| Published in |
Nature, July 2004
|
| DOI | 10.1038/nature02634 |
| Pubmed ID | |
| Authors |
Susan J. Hespos, Elizabeth S. Spelke |
| Abstract |
Because human languages vary in sound and meaning, children must learn which distinctions their language uses. For speech perception, this learning is selective: initially infants are sensitive to most acoustic distinctions used in any language, and this sensitivity reflects basic properties of the auditory system rather than mechanisms specific to language; however, infants' sensitivity to non-native sound distinctions declines over the course of the first year. Here we ask whether a similar process governs learning of word meanings. We investigated the sensitivity of 5-month-old infants in an English-speaking environment to a conceptual distinction that is marked in Korean but not English; that is, the distinction between 'tight' and 'loose' fit of one object to another. Like adult Korean speakers but unlike adult English speakers, these infants detected this distinction and divided a continuum of motion-into-contact actions into tight- and loose-fit categories. Infants' sensitivity to this distinction is linked to representations of object mechanics that are shared by non-human animals. Language learning therefore seems to develop by linking linguistic forms to universal, pre-existing representations of sound and meaning. |
Mendeley readers
The data shown below were compiled from readership statistics for 394 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 18 | 5% |
| Germany | 5 | 1% |
| United Kingdom | 4 | 1% |
| France | 3 | <1% |
| Switzerland | 3 | <1% |
| Australia | 2 | <1% |
| South Africa | 2 | <1% |
| Spain | 2 | <1% |
| Italy | 2 | <1% |
| Other | 7 | 2% |
| Unknown | 346 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 107 | 27% |
| Researcher | 65 | 16% |
| Professor | 37 | 9% |
| Student > Bachelor | 36 | 9% |
| Professor > Associate Professor | 34 | 9% |
| Other | 93 | 24% |
| Unknown | 22 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 196 | 50% |
| Linguistics | 38 | 10% |
| Agricultural and Biological Sciences | 31 | 8% |
| Computer Science | 18 | 5% |
| Social Sciences | 16 | 4% |
| Other | 58 | 15% |
| Unknown | 37 | 9% |
Attention Score in Context
This research output has an Altmetric Attention Score of 16. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 July 2010.
All research outputs
#1,989,491
of 23,680,154 outputs
Outputs from Nature
#41,411
of 92,771 outputs
Outputs of similar age
#2,628
of 54,802 outputs
Outputs of similar age from Nature
#76
of 343 outputs
Altmetric has tracked 23,680,154 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 92,771 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 100.8. This one has gotten more attention than average, scoring higher than 55% of its peers.
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We're also able to compare this research output to 343 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.