La micro-constructionnalisation en tandem : la copularisation de tourner et virer LANGUE FRANÇAISE 1 rticle on line rticle on line "06_VanWettere-Lauwers_4" (Col. : RevueLangueFrançaise
This article aims to evaluate how and to what extent metadata of datasets indexed in DataCite offer clear human-or machine-readable information that enables the research data to be linked to a particular research institution. Two main pathways are explored. First, researchers can encode their affiliation information at the moment of data submission. This can be done by means of free-text metadata fields or via the inclusion of identifiers such as GRID/ROR and ORCID. Second, affiliation information can be traced indirectly through linking between a dataset and associated publications, given that the metadata of publications is often more explicit about affiliation information than the metadata of datasets. Both pathways of affiliation information encoding are evaluated on the basis of metadata pertaining to datasets created at the five Flemish universities. It is shown that good practices such as encoding of affiliation information in a dedicated metadata field or inclusion of ORCID in the metadata are on the rise, but could be expanded further. Finally, the establishment of links between datasets and related publications is often lacking in dataset metadata, although there are important differences between data repositories, as is also demonstrated in a more data-intensive follow-up analysis based on random samples of metadata records. It is important that data repositories address this issue by providing a metadata field clearly dedicated to associated publications, prominently displayed on the landing page of the dataset.
This paper examines the productivity of the subject complement slot in a set of French and Dutch (semi-)copular micro-constructions. The presumed counterpart of productivity, conventionalization in the form of high token frequency, will also be taken into account in the analysis of the productivity complex. On the one hand, it will be shown that prototypical copulas generally have a higher productivity than semi-copulas, although there are some semi-copulas that can rival the productivity of prototypical copulas. On the other hand, it will be demonstrated that high token frequency is in general detrimental to productivity, on the level of the entire subject complement slot and on the level of the different semantic classes. However, the shape of the frequency distribution also seems to play a role: multiple highly frequent types are in my data more detrimental to productivity than one extremely frequent type, although the semantic connectedness of the types in the distribution might also be an explanatory factor.
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