Expanding a Professional Learning Community to Focus on Inclusion, Belonging, and Student Success
Bibliographic record
Abstract
Student success, particularly for students from marginalized populations, depends on a number of co-existing factors, not the least of which are a sense of belonging and the institution’s focus on inclusion. This article showcases the lessons learned from a professional learning community (PLC) for faculty, staff, and students, which was intentionally designed to create awareness of these issues and the need for courageous conversations to support change. The article discusses one particular PLC, a form of virtual “book club,” which occurred during the Fall 2021 semester (September–December). This PLC was focused on Anthony Jack’s text The Privileged Poor: How Elite Colleges Are Failing Disadvantaged Students, published in 2019, and encouraged a unique dialogue on student experience, co-facilitated by a team who critiqued aspects such as race, class, and first-generation status from different vantage points in higher education.
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.
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 | 0.024 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.021 | 0.018 |
| Scholarly communication | 0.018 | 0.013 |
| Open science | 0.003 | 0.050 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.011 | 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".