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Record W4313241278 · doi:10.1093/ae/tmac071

How Welcoming Is Your Workspace?

2022· article· en· W4313241278 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAmerican Entomologist · 2022
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsnot available
Fundersnot available
KeywordsWorkspaceComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

For a space where scientists spend a considerable amount of time, the laboratory is often a lackluster environment. We’ve all seen labs cluttered with egregious piles of equipment or strewn with Fischer Scientific catalogs and potentially useful Styrofoam boxes, the lab doors bare aside from a list of emergency contacts, and, if you’re lucky, a few cut-out photographs from last year’s Entomological Society of America insect calendar. More importantly, how often are new lab members reliant on the wisdom of the long-term technician or postdoc to find the new sleeves of Petri dishes or the large-sized gloves amidst the chaos of an unorganized space? We believe the setting in which we work can have a significant impact on our well-being. We feel most scientifically creative and productive when we’re safe and supported in our lab environment. The lab environment is not just the physical space that we occupy; it represents the lab community and its values. Though there is a certain charm to a dingy but well-loved space, there are many tangible ways to make a lab space and lab community feel more open and inviting. Share information between lab members. Label equipment and storage areas, create digital repositories, and make a lab directory with contact information. This lessens the knowledge gap between new and senior members of the lab, as well as keeping the lab organized and functioning smoothly. Consider how your lab communicates. We have found that the messaging app Slack works well, that channels set for storing lab protocols, ordering information, colony care, and even fun channels for sharing recipes and memes. Develop a safety stash for your lab. We were inspired to do so by a tweet from Dr. Tera Levin at the University of Pittsburgh. Ours has pain medication, cough drops, toiletries, hair ties, emergency lunch options, and sweet treats. Post stickers, posters, or notes that reflect the values of your lab. Pictured above, the entrance to the Hermann Lab of Arthropod Ecology and Trophic Interactions includes stickers of our study organisms, reminders that it’s okay to not be okay, photos of the lab doing fieldwork, and a massive Pride flag. Institute a “crappy/happy” introduction into your lab meetings. At the start of our lab meetings, we all share one crappy thing and one happy thing from the week, which has been a great bonding tool for all lab members (including the undergraduates) and highlights our shared struggles. Take workshops together on diversity, equity, and inclusion in your workspace. At our home institution, we have the Rainbow Network, which allows prospective students to readily identify research groups where faculty and lab members have received training on LGBTQ+ issues and are committed to inclusivity. Incorporate group lab readings that show how DEI can be integrated into the lab space. This offers an opportunity for all members of the lab to feel welcome and prompts conversations about inclusivity and equity in your space. Recommended papers include McGill et al. 2021 (“You Are Welcome Here: A Practical Guide to Diversity, Equity, and Inclusion for Undergraduates Embarking on an Ecological Research Experience”) and Chaudhury et al. 2020 (“Next Steps in Dismantling Discrimination: Lessons from Ecology and Conservation Science”). Create a field safety plan specific to your lab’s needs with inclusivity in mind. At the beginning of the summer, we sat as a group with our new crop of undergraduates to devise a field safety plan for any situations that might arise and facilitated an honest conversation about the intersection of race/ gender identity and field safety. (Part of this included drafting a step-by-step guide for what to do if pulled over by the police.) Our lab at Penn State provides bright field safety vests adorned with the PSU logo so that all lab members can be easily identified in the field. On field sampling days, we communicate which lab members are participating and share the addresses of the sampling sites. Though these steps may seem inconsequential compared to the structural change needed in scientific institutions to guide our community toward inclusivity and equity, change can start with how you maintain your lab environment. Lillian Germeroth (M.S. student) and Jess Kansman (postdoc fellow) are members of the Hermann Arthropod Ecology and Trophic Interactions Lab (PI Sara Hermann) at Penn State University in University Park, PA. This article is written to reflect the development of community and inclusivity efforts in the Hermann lab.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.592
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.128
GPT teacher head0.484
Teacher spread0.356 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it