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Transparency in qualitative research: Increasing fairness in the CHI review process

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

Standard

Transparency in qualitative research : Increasing fairness in the CHI review process. / Talkad Sukumar, Poorna; Avellino, Ignacio; Remy, Christian et al.

CHI EA 2020 - Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems. Honolulu : Association for Computing Machinery, 2020. 3381066 (Conference on Human Factors in Computing Systems - Proceedings).

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

Harvard

Talkad Sukumar, P, Avellino, I, Remy, C, Devito, MA, Dillahunt, TR, McGrenere, J & Wilson, ML 2020, Transparency in qualitative research: Increasing fairness in the CHI review process. in CHI EA 2020 - Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems., 3381066, Association for Computing Machinery, Honolulu, Conference on Human Factors in Computing Systems - Proceedings, 2020 ACM CHI Conference on Human Factors in Computing Systems, CHI EA 2020, Honolulu, United States, 25/04/2020. https://doi.org/10.1145/3334480.3381066

APA

Talkad Sukumar, P., Avellino, I., Remy, C., Devito, M. A., Dillahunt, T. R., McGrenere, J., & Wilson, M. L. (2020). Transparency in qualitative research: Increasing fairness in the CHI review process. In CHI EA 2020 - Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems [3381066] Association for Computing Machinery. Conference on Human Factors in Computing Systems - Proceedings https://doi.org/10.1145/3334480.3381066

CBE

Talkad Sukumar P, Avellino I, Remy C, Devito MA, Dillahunt TR, McGrenere J, Wilson ML. 2020. Transparency in qualitative research: Increasing fairness in the CHI review process. In CHI EA 2020 - Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems. Honolulu: Association for Computing Machinery. Article 3381066. (Conference on Human Factors in Computing Systems - Proceedings). https://doi.org/10.1145/3334480.3381066

MLA

Talkad Sukumar, Poorna et al. "Transparency in qualitative research: Increasing fairness in the CHI review process". CHI EA 2020 - Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems. Honolulu: Association for Computing Machinery. (Conference on Human Factors in Computing Systems - Proceedings). 2020. https://doi.org/10.1145/3334480.3381066

Vancouver

Talkad Sukumar P, Avellino I, Remy C, Devito MA, Dillahunt TR, McGrenere J et al. Transparency in qualitative research: Increasing fairness in the CHI review process. In CHI EA 2020 - Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems. Honolulu: Association for Computing Machinery. 2020. 3381066. (Conference on Human Factors in Computing Systems - Proceedings). doi: 10.1145/3334480.3381066

Author

Talkad Sukumar, Poorna ; Avellino, Ignacio ; Remy, Christian et al. / Transparency in qualitative research : Increasing fairness in the CHI review process. CHI EA 2020 - Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems. Honolulu : Association for Computing Machinery, 2020. (Conference on Human Factors in Computing Systems - Proceedings).

Bibtex

@inproceedings{91a33b076c1e456286695dfc0e20338e,
title = "Transparency in qualitative research: Increasing fairness in the CHI review process",
abstract = "Transparency in process and its reporting is paramount for establishing the rigor of qualitative studies. However, the CHI conference receives submissions with varying levels of transparency and oftentimes, papers that are more transparent can be inadvertently subjected to more scrutiny in the review process, raising issues of fairness. In this panel, we bring together researchers with diverse qualitative work experiences to present examples of transparency-related initiatives and their corresponding review responses. We aim to work towards setting standards for transparent reporting in qualitative-work submissions and increasing fairness in the review process. We focus on the challenges in achieving transparency in qualitative research and current workarounds to overcome frictions in the reviewing process through engaging discussions involving panelists and the audience.",
keywords = "Open research, Peer review, Qualitative research, Transparency",
author = "{Talkad Sukumar}, Poorna and Ignacio Avellino and Christian Remy and Devito, {Michael A.} and Dillahunt, {Tawanna R.} and Joanna McGrenere and Wilson, {Max L.}",
year = "2020",
month = apr,
doi = "10.1145/3334480.3381066",
language = "English",
series = "Conference on Human Factors in Computing Systems - Proceedings",
publisher = "Association for Computing Machinery",
booktitle = "CHI EA 2020 - Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems",
address = "United States",
note = "2020 ACM CHI Conference on Human Factors in Computing Systems, CHI EA 2020 ; Conference date: 25-04-2020 Through 30-04-2020",

}

RIS

TY - GEN

T1 - Transparency in qualitative research

T2 - 2020 ACM CHI Conference on Human Factors in Computing Systems, CHI EA 2020

AU - Talkad Sukumar, Poorna

AU - Avellino, Ignacio

AU - Remy, Christian

AU - Devito, Michael A.

AU - Dillahunt, Tawanna R.

AU - McGrenere, Joanna

AU - Wilson, Max L.

PY - 2020/4

Y1 - 2020/4

N2 - Transparency in process and its reporting is paramount for establishing the rigor of qualitative studies. However, the CHI conference receives submissions with varying levels of transparency and oftentimes, papers that are more transparent can be inadvertently subjected to more scrutiny in the review process, raising issues of fairness. In this panel, we bring together researchers with diverse qualitative work experiences to present examples of transparency-related initiatives and their corresponding review responses. We aim to work towards setting standards for transparent reporting in qualitative-work submissions and increasing fairness in the review process. We focus on the challenges in achieving transparency in qualitative research and current workarounds to overcome frictions in the reviewing process through engaging discussions involving panelists and the audience.

AB - Transparency in process and its reporting is paramount for establishing the rigor of qualitative studies. However, the CHI conference receives submissions with varying levels of transparency and oftentimes, papers that are more transparent can be inadvertently subjected to more scrutiny in the review process, raising issues of fairness. In this panel, we bring together researchers with diverse qualitative work experiences to present examples of transparency-related initiatives and their corresponding review responses. We aim to work towards setting standards for transparent reporting in qualitative-work submissions and increasing fairness in the review process. We focus on the challenges in achieving transparency in qualitative research and current workarounds to overcome frictions in the reviewing process through engaging discussions involving panelists and the audience.

KW - Open research

KW - Peer review

KW - Qualitative research

KW - Transparency

UR - http://www.scopus.com/inward/record.url?scp=85090219029&partnerID=8YFLogxK

U2 - 10.1145/3334480.3381066

DO - 10.1145/3334480.3381066

M3 - Article in proceedings

AN - SCOPUS:85090219029

T3 - Conference on Human Factors in Computing Systems - Proceedings

BT - CHI EA 2020 - Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems

PB - Association for Computing Machinery

CY - Honolulu

Y2 - 25 April 2020 through 30 April 2020

ER -