Teacher (Dis)connectedness and burnout during COVID-19
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A mixed methods research design was used to generate a robust understanding of the relationships between teacher burnout and possible protective effects of collegial relationships during the COVID-19 pandemic. Quantitative data from 277 Canadian teachers collected during the second (n = 147) and third waves (n = 130) of the COVID-19 pandemic indicated that, while teachers’ perceptions of their levels of administrative and collegial support and their levels of teacher burnout remained consistent between waves, teachers’ level of connectedness was statistically lower during the third wave. Subsequent qualitative data generated from focus groups of 20 teachers conducted in each wave, as well as bi-weekly interviews of a panel of 21 teachers over the course of the pandemic, help explain the factors that resulted in teachers’ decreased connection. The findings point to teachers' sense of connectedness as a complex construct rather than a sum of relationships.
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.
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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.219 | 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 it