Are Female Applicants Disadvantaged in National Institutes of Health Peer Review? Combining Algorithmic Text Mining and Qualitative Methods to Detect Evaluative Differences in R01 Reviewers' Critiques.
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Are Female Applicants Disadvantaged in National Institutes of Health Peer Review? Combining Algorithmic Text Mining and Qualitative Methods to Detect Evaluative Differences in R01 Reviewers' Critiques.
description
2017 nî lūn-bûn
@nan
2017年の論文
@ja
2017年論文
@yue
2017年論文
@zh-hant
2017年論文
@zh-hk
2017年論文
@zh-mo
2017年論文
@zh-tw
2017年论文
@wuu
2017年论文
@zh
2017年论文
@zh-cn
name
Are Female Applicants Disadvan ...... s in R01 Reviewers' Critiques.
@en
Are Female Applicants Disadvan ...... s in R01 Reviewers' Critiques.
@nl
type
label
Are Female Applicants Disadvan ...... s in R01 Reviewers' Critiques.
@en
Are Female Applicants Disadvan ...... s in R01 Reviewers' Critiques.
@nl
prefLabel
Are Female Applicants Disadvan ...... s in R01 Reviewers' Critiques.
@en
Are Female Applicants Disadvan ...... s in R01 Reviewers' Critiques.
@nl
P2093
P2860
P356
P1476
Are Female Applicants Disadvan ...... s in R01 Reviewers' Critiques.
@en
P2093
Aaron Potvien
Amarette Filut
Anna Kaatz
Anupama Bhattacharya
Dastagiri Malikireddy
Madeline Jens
Molly Carnes
Renee Leatherberry
Wairimu Magua
Xiaojin Zhu
P2860
P304
P356
10.1089/JWH.2016.6021
P577
2017-03-10T00:00:00Z