Interdisciplinary explorations: Setting the stage for change through understanding culture and attending to psychological safety in an Ontario Community College
Bibliographic record
Abstract
Central to this Organizational Improvement Plan is the desire to close the gap between a curriculum that is disciplinary-centric to one that is more interdisciplinary. This change will better prepare college graduates for the future skills required in the workplace where increasingly complex problems require interdisciplinary solutions. While this may, at first, appear to be solely about the curriculum, the problem is that moving from a disciplinary to an interdisciplinary mindset involves disturbing deeply rooted disciplinary boundaries and, in turn, challenging faculty identities. In order to influence the culture of College X towards interdisciplinarity, the cultural context of the institution – as well as of the disciplinary subcultures – will need to be considered. Interdisciplinarity aligns with key priorities identified in the current Strategic Plan of College X and is congruent with the mission and values of the institution. Schein’s (2017) cultural theory provides the theoretical framework for this second-order change. Schein’s (2017) work provides a model for change that attends to psychological safety which is critical when perceptions, values and beliefs are challenged. One of the main tools proposed for creating change is the Community of Transformation model, under the auspices of the Teaching and Learning Centre, augmented by reviewing and rebranding the activities in the Innovation Centre and Applied Research to be more explicitly interdisciplinary. Adaptive and distributed leadership approaches respect the organizational context at College X which values collaboration and consultation and, therefore, provide the leadership framework. Finally, this Organizational Improvement Plan draws upon sensemaking activities in order to ensure effective communication to various stakeholders as they navigate the change proposed at College X.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.044 | 0.019 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".