| 研究課題/領域番号 |
21K02919
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| 研究種目 |
基盤研究(C)
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| 配分区分 | 基金 |
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| 応募区分 | 一般 |
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| 審査区分 |
小区分09080:科学教育関連
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| 研究機関 | 筑波大学 |
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研究代表者 |
Millar Neil 筑波大学, システム情報系, 准教授 (70751981)
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| 研究期間 (年度) |
2021-04-01 – 2025-03-31
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| 研究課題ステータス |
交付 (2022年度)
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| 配分額 *注記 |
3,510千円 (直接経費: 2,700千円、間接経費: 810千円)
2024年度: 650千円 (直接経費: 500千円、間接経費: 150千円)
2023年度: 650千円 (直接経費: 500千円、間接経費: 150千円)
2022年度: 780千円 (直接経費: 600千円、間接経費: 180千円)
2021年度: 1,430千円 (直接経費: 1,100千円、間接経費: 330千円)
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| キーワード | corpus lingusitics / scientific writing / research funding / research ethics / biomedical language / Medical discourse / Medical ethics / Corpus Linguistics |
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| 研究開始時の研究の概要 |
This study assesses the use of 'hype' in funding applications for medical research - i.e. language which promotes positive aspects of the research (e.g. robust, novel, innovative, unprecedented). Findings will help inform review processes and have implications for writers of grant proposals.
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| 研究実績の概要 |
We analysed abstracts describing all research projects funded by the NIH during the period 1985 to 2020 for 'hype' adjectives. We published the findings of these analyses in JAMA Network Open (IF:13.37). The paper generated attention being picked up by news media organisations and the journal Science, and also being covered in a commentary piece in the same journal and an additional article in the Lancet. We conducted a follow up analysis of NIH funding announcements, which we have also published in JAMA Network Open. In addition we presented out work at two international conferences and submitted a linguistic analysis of our data to Applied Linguistics (IF: 4.6). We are constructing a dataset containing abstracts describing all research funded by the NIH during the same period.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
1: 当初の計画以上に進展している
理由
As described above, our results have generated interest in high impact journals. In addition, in order to address questions that have arisen in our analyses, we a currently constructing a dataset that was beyond the scope of about initial proposal.
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| 今後の研究の推進方策 |
We are constructing a corpus of all pubmed abstracts describing research funded by the NIH during the same period. We will analyse hype in the data and publish finding in both medical and linguistics journals.
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