Canadian Academic Library Leadership (CALL): The State of Equity
Bibliographic record
Abstract
Leadership is a vast, complex, and heavily examined concept in many fields. The concept of leadership has evolved, and definitions are ubiquitous, subjective, socially constructed, and influenced by many aspects such as the environment and culture. Since knowing leadership can come from multiple perspectives, it is important to have a space for minority librarians and their styles and unique strengths in academic library leadership. Equitable and inclusive leadership is critical to sustaining leadership in librarianship; it would mean providing leadership space for minority librarians, accepting their strengths, sponsoring them for leadership positions, and overhauling the leadership curriculum and academic library leadership practices. Despite some attempts, librarianship has been slow to progress on inclusive leadership and there are few successful pathways for minority librarians in academic leadership positions. The lack of intentional opportunities for (Black, Indigenous, and persons of colour) BIPOC librarians, sexual minority librarians, and librarians with disabilities to serve as leaders provides a platform to discuss library leadership as an inequitable issue and this research is a CALL (Canadian Academic Library Leadership) to attend to the state of equity in library leadership. Understanding the leadership journey undertaken by current minority library leaders will enhance the understanding of inclusion efforts. This study undertook a comprehensive approach to the presence and absence of minority librarians in leadership positions in Canadian academic libraries by using a combination of critical race theory and appreciative inquiry. Critical race theory (CRT) is broader than just race and helps to critically evaluate marginalization based on, for example, race, gender, tribe, or sexuality, from a critical, emancipatory, and social justice lens. Appreciative inquiry lent a positive perspective and helped frame the research questions to encourage all participants to share their stories through a success perspective, which might help create opportunities for more minority librarians. Findings from all phases of participants provided valuable insights into self-efficacy and capacity-building measures undertaken by minority librarians; and, highlighted academic library structures, systems, policies, and other institutional elements that need to shift, unlearn, and relearn, to aid minority librarians in their leadership journey.
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.034 | 0.017 |
| Scholarly communication | 0.019 | 0.006 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".