Margaret E. Brooks

909 total citations
23 papers, 635 citations indexed

About

Margaret E. Brooks is a scholar working on Sociology and Political Science, Organizational Behavior and Human Resource Management and General Decision Sciences. According to data from OpenAlex, Margaret E. Brooks has authored 23 papers receiving a total of 635 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Sociology and Political Science, 7 papers in Organizational Behavior and Human Resource Management and 5 papers in General Decision Sciences. Recurrent topics in Margaret E. Brooks's work include Social and Intergroup Psychology (6 papers), Decision-Making and Behavioral Economics (5 papers) and Corporate Identity and Reputation (4 papers). Margaret E. Brooks is often cited by papers focused on Social and Intergroup Psychology (6 papers), Decision-Making and Behavioral Economics (5 papers) and Corporate Identity and Reputation (4 papers). Margaret E. Brooks collaborates with scholars based in United States and Singapore. Margaret E. Brooks's co-authors include Scott Highhouse, Steven S. Russell, David C. Mohr, Kevin Nolan, Dev K. Dalal, Charlie L. Reeve, Michael A. Lodato, Shuang Yueh Pui, Yuyan Zhang and Don C. Zhang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Applied Psychology and Journal of Management.

In The Last Decade

Margaret E. Brooks

23 papers receiving 604 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Margaret E. Brooks United States 13 254 232 146 86 83 23 635
Duanxu Wang China 10 214 0.8× 464 2.0× 141 1.0× 44 0.5× 86 1.0× 32 721
Fred R. Blass United States 8 114 0.4× 315 1.4× 155 1.1× 31 0.4× 77 0.9× 10 553
Björn Michaelis Germany 10 195 0.8× 346 1.5× 85 0.6× 48 0.6× 68 0.8× 12 610
Lilian Otaye‐Ebede United Kingdom 9 145 0.6× 306 1.3× 169 1.2× 41 0.5× 192 2.3× 19 654
Gabriele Jacobs Netherlands 13 155 0.6× 322 1.4× 239 1.6× 111 1.3× 70 0.8× 31 694
Mary Dana Laird United States 11 102 0.4× 306 1.3× 176 1.2× 54 0.6× 58 0.7× 18 529
Marjo‐Riitta Diehl Finland 10 167 0.7× 221 1.0× 126 0.9× 75 0.9× 82 1.0× 22 544
James B. Oldroyd United States 10 151 0.6× 224 1.0× 135 0.9× 34 0.4× 35 0.4× 16 534
Sudhir K. Saha Canada 10 124 0.5× 262 1.1× 79 0.5× 53 0.6× 54 0.7× 20 543
Julia Backmann Germany 11 206 0.8× 187 0.8× 72 0.5× 31 0.4× 42 0.5× 21 601

Countries citing papers authored by Margaret E. Brooks

Since Specialization
Citations

This map shows the geographic impact of Margaret E. Brooks's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Margaret E. Brooks with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Margaret E. Brooks more than expected).

Fields of papers citing papers by Margaret E. Brooks

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Margaret E. Brooks. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Margaret E. Brooks. The network helps show where Margaret E. Brooks may publish in the future.

Co-authorship network of co-authors of Margaret E. Brooks

This figure shows the co-authorship network connecting the top 25 collaborators of Margaret E. Brooks. A scholar is included among the top collaborators of Margaret E. Brooks based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Margaret E. Brooks. Margaret E. Brooks is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Highhouse, Scott & Margaret E. Brooks. (2023). Interpreting the magnitude of predictor effect sizes: It is time for more sensible benchmarks. Industrial and Organizational Psychology. 16(3). 332–335. 1 indexed citations
2.
Lee, Soomi, et al.. (2023). Working and working out: Decision-making inputs connect daily work demands to physical exercise.. Journal of Occupational Health Psychology. 28(3). 160–173. 3 indexed citations
3.
Highhouse, Scott, et al.. (2022). Culture versus other sources of variance in risk and benefit perceptions: A comparison of Japan and the United States. Journal of Behavioral Decision Making. 35(5). 3 indexed citations
4.
Highhouse, Scott & Margaret E. Brooks. (2022). Improving Workplace Judgments by Reducing Noise: Lessons Learned from a Century of Selection Research. Annual Review of Organizational Psychology and Organizational Behavior. 10(1). 519–533. 9 indexed citations
5.
Highhouse, Scott, et al.. (2021). Apples, oranges, and ironing boards: Comparative effect sizes influence lay impressions of test validity. International Journal of Selection and Assessment. 30(2). 230–235. 3 indexed citations
6.
Highhouse, Scott & Margaret E. Brooks. (2021). A simple solution to a complex problem: Manipulate the mediator!. Industrial and Organizational Psychology. 14(4). 493–496. 6 indexed citations
7.
O’Neil, Deborah A., Margaret E. Brooks, & Margaret M. Hopkins. (2018). Women’s roles in women’s career advancement: what do women expect of each other?. Career Development International. 23(3). 327–344. 12 indexed citations
8.
Highhouse, Scott, et al.. (2017). Is a .51 validity coefficient good? Value sensitivity for interview validity. International Journal of Selection and Assessment. 25(4). 383–389. 18 indexed citations
9.
Highhouse, Scott & Margaret E. Brooks. (2017). Straight Talk About Selecting for Upper Management. Oxford University Press eBooks. 1 indexed citations
10.
Brooks, Margaret E., Dev K. Dalal, & Kevin Nolan. (2013). Are common language effect sizes easier to understand than traditional effect sizes?. Journal of Applied Psychology. 99(2). 332–340. 51 indexed citations
11.
Brooks, Margaret E.. (2011). Management indecision. Management Decision. 49(5). 683–693. 24 indexed citations
12.
Lodato, Michael A., Scott Highhouse, & Margaret E. Brooks. (2011). Predicting professional preferences for intuition‐based hiring. Journal of Managerial Psychology. 26(5). 352–365. 32 indexed citations
13.
14.
Brooks, Margaret E., et al.. (2010). Signals of Employer Impressiveness and Respectability to Job Market Entrants. Corporate Reputation Review. 13(3). 172–183. 12 indexed citations
15.
Brooks, Margaret E., et al.. (2009). Distinction Bias in Applicant Reactions to Using Diversity Information in Selection. International Journal of Selection and Assessment. 17(4). 377–390. 13 indexed citations
16.
Highhouse, Scott, et al.. (2009). An Organizational Impression Management Perspective on the Formation of Corporate Reputations. Journal of Management. 35(6). 1481–1493. 223 indexed citations
17.
Maynard, Douglas C. & Margaret E. Brooks. (2008). The Persistence of Stereotypes in the Context of Familiarity. Industrial and Organizational Psychology. 1(4). 417–419. 4 indexed citations
18.
Brooks, Margaret E. & Scott Highhouse. (2006). Familiarity Breeds Ambivalence. Corporate Reputation Review. 9(2). 105–113. 32 indexed citations
19.
Reeve, Charlie L., Scott Highhouse, & Margaret E. Brooks. (2006). A Closer Look at Reactions to Realistic Recruitment Messages. International Journal of Selection and Assessment. 14(1). 1–15. 35 indexed citations
20.
Brooks, Margaret E., Scott Highhouse, Steven S. Russell, & David C. Mohr. (2003). Familiarity, ambivalence, and firm reputation: Is corporate fame a double-edged sword?. Journal of Applied Psychology. 88(5). 904–914. 110 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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