CCEM's Strategic Initiatives and Collaborative Approach to Advancing Equity, Diversity, and Inclusion in STEAM Fields
Bibliographic record
Abstract
Equity, diversity, and inclusion (EDI) constitute fundamental priorities at the Canadian Centre for Electron Microscopy (CCEM), underscoring its commitment to fostering an environment of inclusive excellence within the electron microscopy (EM) field. CCEM endeavors to dismantle systemic barriers and extend its outreach to underrepresented groups across all facets of governance, management, and operational domains. Under the guidance of McMaster University's Associate Vice-President for Equity and Inclusion, CCEM has crafted a Framework for EDI, with the aim of intentionally identifying and achieving institution-wide objectives in this realm [1]. To make long lasting differences in the diversity of science, technology, engineering, arts, and mathematics (STEAM) fields, CCEM is committed to engaging key stakeholders of all levels such as its Governing Board, Management team, partners, and outreach groups to name a few. The specifics of CCEM’s ambitions lie in its Strategic Plan [2] and EDI Framework [3]. To date, highlights of CCEM’s action items related to EDI drivers and promotion include: NextGen Microscopist Program: This initiative seeks to ignite interest in STEAM disciplines among youth from kindergarten to twelfth grade by providing complimentary access to a table-top scanning electron microscope and associated educational resources, with a particular emphasis on engaging underrepresented youth demographics within Canada [4]. Management and Staff Training: Ensuring all management and staff undergo training through McMaster course offerings on EDI and communication to build organizational awareness. CCEM Academy with focus on EDI: The EDI paradigm is integrally woven into CCEM's education through the Academy, informing curriculum design, speaker/instructor selection processes, and the overarching commitment to ensuring accessibility across all educational content, both offline and online. Human Resource Practices: CCEM is committed to following best practices in hiring and promoting a safe and accessible workplace through external consultations and Management specific training in equitable hiring practices. The ongoing journey toward realizing these initiatives has been marked by both successes and challenges, the insights gleaned from which CCEM is eager to share with the broader community of likeminded institutions. By fostering an ongoing dialogue surrounding EDI best practices, CCEM seeks to catalyze continuous improvement and collectively advance the cause of inclusivity within the scientific community.
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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 | 0.036 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".