Evidence map›Paper›PMID 41287455›Full record

ArticleChembiochem : a European journal of chemical biology2025

Practical Tips for Intentional and Inclusive Recruiting and Hiring for Academic Research Laboratories.

Madison K C Seto, Taiasean Wu, Aaron M Leconte

Abstract read
In one paragraph

Article in Chembiochem : a European journal of chemical biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Madison K C SetoDepartment of Natural Sciences, Pitzer and Scripps Colleges, 925 N Mills Avenue, Claremont, California, 91711, USA.
Taiasean WuDepartment of Natural Sciences, Pitzer and Scripps Colleges, 925 N Mills Avenue, Claremont, California, 91711, USA.
Aaron M LeconteDepartment of Natural Sciences, Pitzer and Scripps Colleges, 925 N Mills Avenue, Claremont, California, 91711, USA.ORCID https://orcid.org/0000-0002-5789-9147

Funding

Research Corporation for Science Advancement #27504
6 · The paper itself

Abstract

Hiring decisions are some of the most important choices PIs make for their research groups. Whether it is undergraduates, graduate students, postdoctoral researchers, or other research assistants, trainees are pivotal for the success of a research group. Choosing an effective team can lead to synergy amongst researchers, high creativity, and groundbreaking science. Choosing an ineffective team can lead to infighting, toxicity, low morale, and scientific stagnation. These same hiring decisions are critical in creating an equitable and inclusive lab environment. Importantly, the challenges for creating productive and inclusive lab groups align: both can be achieved by 1) advertising broadly to ensure a high number of qualified potential researchers apply and 2) removing unconscious selection bias in the hiring process such that these highly qualified researchers are hired. Intentionally and deliberately incorporating these steps into the recruiting and selection processes aids in the recruitment of a more effective and inclusive research team. Herein, practical advice for recruiting for academic research labs are described. We focus on three areas: advertising your research positions, assessing candidates for research positions, and assessing your hiring practices. In each, we give guiding principles and practical tips for designing an equitable and inclusive hiring process .

Indexed as

LaboratoriesPersonnel SelectionResearch PersonnelHumansequityhiringinclusivitylab management

Identifiers

PMID41287455
PMCPMC12703456

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.