Unknown

Dataset Information

0

Acknowledgements are not just thank you notes: A qualitative analysis of acknowledgements content in scientific articles and reviews published in 2015.


ABSTRACT: Acknowledgements in scientific articles can be described as miscellaneous, their content ranging from pre-formulated financial disclosure statements to personal testimonies of gratitude. To improve understanding of the context and various uses of expressions found in acknowledgements, this study analyses their content qualitatively. The most frequent noun phrases from a Web of Science acknowledgements corpus were analysed to generate 13 categories. When 3,754 acknowledgement sentences were manually coded into the categories, three distinct axes emerged: the contributions, the disclaimers, and the authorial voice. Acknowledgements constitute a space where authors can detail the division of labour within collaborators of a research project. Results also show the importance of disclaimers as part of the current scholarly communication apparatus, an aspect which was not highlighted by previous analyses and typologies of acknowledgements. Alongside formal disclaimers and acknowledgements of various contributions, there seems to remain a need for a more personal space where the authors can speak for themselves, in their own name, on matters they judge worth mentioning.

SUBMITTER: Paul-Hus A 

PROVIDER: S-EPMC6922370 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

altmetric image

Publications

Acknowledgements are not just thank you notes: A qualitative analysis of acknowledgements content in scientific articles and reviews published in 2015.

Paul-Hus Adèle A   Desrochers Nadine N  

PloS one 20191219 12


Acknowledgements in scientific articles can be described as miscellaneous, their content ranging from pre-formulated financial disclosure statements to personal testimonies of gratitude. To improve understanding of the context and various uses of expressions found in acknowledgements, this study analyses their content qualitatively. The most frequent noun phrases from a Web of Science acknowledgements corpus were analysed to generate 13 categories. When 3,754 acknowledgement sentences were manua  ...[more]

Similar Datasets

| S-EPMC4981102 | biostudies-literature
| S-EPMC3058057 | biostudies-literature
| S-EPMC7380499 | biostudies-literature
| S-EPMC7201971 | biostudies-literature
| S-EPMC9718046 | biostudies-literature
| S-EPMC9730209 | biostudies-literature
| S-EPMC5400886 | biostudies-literature
| S-EPMC8691640 | biostudies-literature
| S-EPMC10888521 | biostudies-literature
| S-EPMC7787447 | biostudies-literature