Shifting the Working/Teaching Environment: A Transdisciplinary Perspectives
Bibliographic record
Abstract
Our presentation is based on our study on the “Effects of Covid-19 on Teaching, and Learning: Stories of Racialized Faculty Members and Students''. This was a qualitative narrative study and we conducted focus group discussions and individual interviews. We employed snowballing techniques to recruit study participants. We invited 32 racialized students (domestic and international) and 10 racialized faculty members. The results of this research will be published in a co-edited book and will also invite media houses to feature the results of the project to bring awareness to issues of equity, diversity, and inclusion in the classroom and school environment. The objective of this study was to understand deeper the experiences of racialized faculty members and students and how they have navigated their racialized positions within the on-going pandemic. Covid-19 has affected and compounded issues faced by Racialized populations in ways that have affected their education. On top of inaccessible classrooms and a curriculum that is foreign to them, many racialized students and educators have to deal with inaccessibility of the virtual class because of lack of strong internet connection; mental health issues brought about by the effect of Covid-19 on racialized communities. This oral presentation is to address the question on “how do we shift the working and teaching environments from multidisciplinary to transdisciplinary”? How can we teach, learn, and work; knowing well that care in teaching, working, and learning has contributed to spatial elimination of some students and faculty members who look different because of race, class, gender, sexual orientation or other social markers? This presentation will focus on understanding the unique experience of racialized faculty members and students in the age of virtualized learning and teaching. This presentation pays attention to the ethics of equity, diversity, and equity when it comes to care in a virtual classroom. It seeks to expand these existing multidisciplinary to transdisciplinary forms of care in order to address the working/teaching environment. This presentation attempts to understand racialized educators and student’s everyday experiences in terms of accessibility to virtual classrooms and the curriculum. The objective of this presentation is to present the experiences of racialized faculty members and students and how they navigate their racialized positions within the on-going pandemic. In our presentation we will focus on the findings of our study. The following themes will define our presentation :(1) the different educational experiences of racialized students and educators during Covid-19 pandemic; (2.) the challenges and success racialized educators and students have faced in a virtual classroom during Covid-19 pandemic; and (3.) the different ways in which the racialized students and educators have negotiated the challenges of virtual classrooms during Covid-19 pandemic. We will also include a discussion of our research design that is focused on qualitative narrative study. Then, we conclude.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| 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".