The Cultivation of Systemness for Enhanced Equity, Diversity and Inclusivity at a Mid-sized District School Board in the Province of Ontario
Bibliographic record
Abstract
The cultivation of systemness for enhanced equity, diversity and inclusivity at a mid-sized district school board in the province of Ontario is addressed. The development of shared mindsets regarding a small number of ambitious goals (system coherence) and the implementation of administrative processes such as policies, procedures, practices and protocols (system alignment) that support the optimization of the multi-year strategic plan may, at times, prove difficult to achieve, especially as it relates to bias awareness and critical consciousness, as well as ameliorated fairness and impartiality throughout the organization. Viewed constructively as an opportunity for organizational improvement towards enhanced equity, diversity and inclusivity, strategies to facilitate the elimination of all forms of discrimination and the removal of systemic barriers to learning are explored. A seven-step model for effective change management is utilized as the framework to lead the change process to address the lack of coherence and alignment between the key categories of the annual action plan for equity and anti-racism, and, the goal statements of the empowering equity priority of the multi-year strategic plan for the district. As a tool that utilizes a blend of face-to-face and digital interactions to collect, communicate, collaborate and create with colleagues, professional learning networks (PLNs) are the selected solution to address the problem of practice. PLNs are endorsed as an innovative, forward-thinking approach for knowledge mobilization and solution generation in public education (Briscoe et al., 2015; Trust et al., 2016; Whitby, 2013).\nKeywords: systemness, alignment, coherence, equity, diversity, inclusivity, professional learning networks
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".