From Intent to Action: Reconciliation and Inclusion in Three Canadian Academic Libraries
Bibliographic record
Abstract
A sense of belonging and inclusion creates conditions for individuals and organizations to thrive. Many Canadian university libraries have been initiating actions which advance reconciliation with Indigenous communities in Canada, and to support equity, diversity, inclusion and belonging. Efforts to operationalize reconciliation and inclusion share important qualities yet require distinctive approaches due to historic and contemporary factors. Reconciliation in Canada must recognize the significance and centrality of the land to Indigenous communities. While inclusion strives to more broadly create conditions in which individuals may thrive, with a focus on those from groups who have historically faced systemic barriers. For both reconciliation and inclusion, progress means creating a greater sense of belonging in libraries for both library staff and library users. As organizations, how do we go about making these cultural changes in a sustained and sustainable manner? In this session, three university libraries will briefly share their approaches in “operationalizing” culture change. In each case, organizational practices, structures and strategies will reflect a particular cultural landscape, institutional priorities, and regional history, but situated within an overall Canadian context, and precipitated by specific catalyzing events, such as the Truth and Reconciliation Commission of Canada, instances of anti-black racism, among others. Despite differences, a sense of urgency and momentum have driven work in each of the institutions, yet also increasingly observed are moments of fatigue, despair, apathy, and inertia. The short presentations will be followed by table discussions to share ideas and reflect on how we can support each other in this work.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| 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".