The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Structure and Grammaticalization of Serial Verb Constructions in Sign Language of the Netherlands—A Corpus-Based Study
|
|---|---|
| Published in |
Frontiers in Psychology, July 2018
|
| DOI | 10.3389/fpsyg.2018.00993 |
| Pubmed ID | |
| Authors |
Sascha Couvee, Roland Pfau |
| Abstract |
In serial verb constructions (SVCs), multiple independent lexical verbs are combined in a mono-clausal construction. SVCs express a range of grammatical meanings and are attested in numerous spoken languages all around the world. Yet, to date only few studies have investigated the existence and functions of SVCs in sign languages. For the most part, these studies-including a previous study on Sign Language of the Netherlands (NGT)-relied on elicited data. In this article, we offer a cross-modal typological contribution to the study of SVCs by investigating the phenomenon based on naturalistic corpus data from NGT. A search of the Corpus NGT yielded 41 mono-clausal utterances in which one of a closed set of verbs-namely go, give, take, and call-combines with another lexical verb. While the combinations we found are in important respects reminiscent of SVCs described for spoken languages, our data also confirm the previous finding that the fixed verb in the SVC serves to express agreement (by means of spatial modulation) when the other verb cannot do so. In addition, we identified some novel uses of the verbs go and give: (i) go functioning as a future tense marker and (ii) give functioning as a light verb. We will also discuss aspects of the grammaticalization of SVCs in NGT: from lexical verb to light verb to auxiliary, again offering some comparison to grammaticalization paths described for spoken languages. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 25% |
| Switzerland | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 17 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 29% |
| Student > Master | 4 | 24% |
| Student > Postgraduate | 3 | 18% |
| Librarian | 1 | 6% |
| Other | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 3 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Linguistics | 7 | 41% |
| Social Sciences | 3 | 18% |
| Arts and Humanities | 2 | 12% |
| Computer Science | 1 | 6% |
| Business, Management and Accounting | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 3 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 17 July 2018.
All research outputs
#15,002,907
of 23,079,238 outputs
Outputs from Frontiers in Psychology
#16,347
of 30,437 outputs
Outputs of similar age
#179,409
of 296,581 outputs
Outputs of similar age from Frontiers in Psychology
#514
of 720 outputs
Altmetric has tracked 23,079,238 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 30,437 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.5. This one is in the 38th percentile – i.e., 38% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 296,581 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 720 others from the same source and published within six weeks on either side of this one. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.