Dataset Information

Uncovering Patterns in Reviewers' Feedback to Scene Description Authors.

ABSTRACT: Audio descriptions (ADs) can increase access to videos for blind people. Researchers have explored different mechanisms for generating ADs, with some of the most recent studies involving paid novices; to improve the quality of their ADs, novices receive feedback from reviewers. However, reviewer feedback is not instantaneous. To explore the potential for real-time feedback through automation, in this paper, we analyze 1, 120 comments that 40 sighted novices received from a sighted or a blind reviewer. We find that feedback patterns tend to fall under four themes: (i) Quality; commenting on different AD quality variables, (ii) Speech Act; the utterance or speech action that the reviewers used, (iii) Required Action; the recommended action that the authors should do to improve the AD, and (iv) Guidance; the additional help that the reviewers gave to help the authors. We discuss which of these patterns could be automated within the review process as design implications for future AD collaborative authoring systems.

SUBMITTER: Natalie R

PROVIDER: S-EPMC8855355 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Uncovering Patterns in Reviewers' Feedback to Scene Description Authors.

Natalie Rosiana R Inn Jolene Loh Kar JLK Suen Tan Huei TH Hao Joshua Tseng Shi JTS Kacorri Hernisa H Hara Kotaro K

ASSETS. Annual ACM Conference on Assistive Technologies 20210101

Audio descriptions (ADs) can increase access to videos for blind people. Researchers have explored different mechanisms for generating ADs, with some of the most recent studies involving paid novices; to improve the quality of their ADs, novices receive feedback from reviewers. However, reviewer feedback is not instantaneous. To explore the potential for real-time feedback through automation, in this paper, we analyze 1, 120 comments that 40 sighted novices received from a sighted or a blind rev ...[more]

PMID: 35187544

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Project description:OBJECTIVE:Many journals permit authors to submit supplementary material for publication alongside the article. We explore the value, use and role of this material in biomedical journal articles from the perspectives of authors, peer reviewers and readers. DESIGN AND SETTING:We conducted online surveys (November-December 2016) of corresponding authors and peer reviewers at 17 BMJ Publishing Group journals in a range of specialities. PARTICIPANTS:Participants were asked to respond to one of three surveys: as authors, peer reviewers or readers. RESULTS:We received 2872/20340 (14%) responses: authors 819/6892 (12%), peer reviewers 1142/6682 (17%) and readers 911/6766 (14%). Most authors submitted (711/819, 87%) and 80% (724/911) of readers reported reading supplementary material with their last article, while 95% (1086/1142) of reviewers reported seeing these materials sometimes. Additional data tables were the most common supplementary material reported (authors: 74%; reviewers: 89%; readers: 67%). A majority in each group indicated additional tables were most useful to readers (61%-77%); 20%-36%?and 3%-4% indicated they were most useful to peer reviewers and journal editors, respectively. Checklists and reporting guidelines showed the opposite: higher proportions of each group regarded these as most useful to journal editors. All three groups favoured the publication of additional tables and figures on the journal's website (80%-83%), with <4% of each group responding that these do not need to be available. Approximately one-fifth (16%-23%) responded that raw study data should be available on the journal's website, while 24%-33% said that these materials should not be made available anywhere. CONCLUSIONS:Authors, peer reviewers and readers agree that supplementary materials are useful. Supplementary tables and figures were favoured over reporting checklists or raw data for reading but not for study replication. Journals should consider the roles, resource costs and strategic placement of supplementary materials to ensure optimal usage and minimise waste. TRIAL REGISTRATION NUMBER:NCT02961036.

Dataset Information

Uncovering Patterns in Reviewers' Feedback to Scene Description Authors.

Publications

Uncovering Patterns in Reviewers' Feedback to Scene Description Authors.

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