Responding to community feedback for supporting diversity in HPC & eResearch
Bibliographic record
Abstract
ABSTRACT / INTRODUCTION In November 2020, an Australasian Chapter of the global organisation Women in High Performance Computing (WHPC) was launched to better support diversity across the Australian and New Zealand HPC and eResearch sectors. As one of the first steps to connect with the community, the Chapter's founding organisations — NeSI, Australasian eResearch Organisations (AeRO), Monash University, NCI Australia, and Pawsey Supercomputing Centre — polled community members on what activities and initiatives they'd like the Chapter focus on in 2021. In this session, we will review the results of that community consultation, discuss how the top-ranked activities can be actioned, as well as dive deeper into what can be learned from past and other initiatives related to mentorship, recruiting & retention, professional development, and community-building for women in HPC and eResearch. ABOUT THE AUTHORJana Makar coordinates a variety of engagement initiatives and external communications to raise the profile of NeSI’s activities, impacts, and collaborations. Prior to joining NeSI, Jana spent more than a decade in communications roles with various organisations in Canada’s digital research infrastructure sector, from provincial research and education networks to regional and national high performance computing platforms. Megan Guidry is the Regional Coordinator for the Carpentries in New Zealand and also coordinates the training activities of New Zealand eScience Infrastructure (NeSI). Her main priority is raising eResearch capability in New Zealand through training delivery and community building. Lucy Guest's passion for STEM began on a sheep farm in Northern NSW where her childhood was spent exploring, experimenting and investigating. The National Youth Science Forum cemented ‘science’ as a career path, and a Bachelor Science/Law undertaken at UNE. It was the NYSF that brought her to Canberra, where she worked as the Marketing and Communications Officer, relishing the opportunity to introduce the joy of STEM to next generations. Lucy joined NCI as their Communications Manager in 2012 and is committed to championing women in HPC. Aidan Muirhead grew up in two Australian territories – the ACT and the NT – as well as Singapore and Serbia. She loved that maths gave her a universal language and has always wanted to know more about how things work. Passion for STEM and sharing stories led her to complete a Bachelor and Graduate Diploma in Science Communication at ANU. After 8 years at Questacon developing and delivering STEM programs across Australia, Aidan moved to NCI in 2019. Aidan is proud to support diversity in HPC, HPD, and eResearch. Kerri Wait's HPC journey began as an electronic engineering student simulating semiconductor devices during an industrial experience placement in Germany. Kerri has worked at a number of HPC and research computing facilities in Australia, collaborating with researchers to deliver scientific research that is faster, less painful, more robust, and repeatable. Kerri attended IBM’s EXITE program as a high school student, returning to speak as an early career professional, and is particularly interested in supporting women from low socioeconomic backgrounds to explore careers in STEM. Aditi Subramanya is a creative marketing and communications professional with more than 10 years’ experience in her chosen profession. She holds a Bachelor of Commerce specialising in Public Relations and Tourism and Event Management. She has been instrumental in providing global visibility in order to showcase Pawsey’s capabilities and services via key exhibitions at conferences worldwide, and plays a pivotal role in increasing market presence and overall brand awareness. Loretta Davis is a seasoned IT professional with 25+ years experience in the eResearch, commercial and government sectors in Australia, Africa and the USA. When not working part time for AeRO, Loretta consults as a Solutions Specialist to a number of private clients. Dr. Jenni Harrison is a passionate leader in technology and a positive role model. Jenni is an inclusive, strategic thinker who leads on national STEM initiatives, whilst mentoring others (presently a mentor for IMNIS and AIM WA). On 30th October 2020, Jenni was recognised by Women in Technology WA as a Tech [+] 20 Award Winner for 2020. Jenni is passionate about women in STEM and inclusion, is a Member of STEM Women, Women in STEMM, UN Women, WiTWA and is a Women in Data Science Ambassador for 2020. Jenni has presented on inclusion in STEM at several international conferences and events. An AICD graduate, with substantial governance experience, Jenni uses her skills to promote inclusion. In this regard Jenni is Chair of SHINE, a remarkable Not for Profit organisation based in the Geraldton region that collaborates with business and schools to actively engage with young female students who are at risk of disengaging from the conventional education system. Jenni is a lifelong learner and published author.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.037 | 0.081 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.006 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.003 | 0.025 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.067 | 0.012 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".