Pandemic digital structural violence: Teachers' observation of post‐pandemic learning loss in students
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
Abstract Almost four academic years have passed since emergency remote teaching (ERT) was employed as a temporary means for continuing education. In the post‐pandemic era, residual impacts from ERT are still unfolding. Teachers reported a pronounced decrease in students' academic performance, concentration and social skills. As time passes, we seem to have forgotten the negative impacts of ERT on students, which affects primary, secondary, and even university students. Using case studies, digital ethnography and autoethnography, this research explores ERT in a private school in Canada and a local Band 3 school in Hong Kong. The qualitative data allow an extensive analysis of the circumstances and outcomes of two diverse groups of students. The findings include class participation as an outcome of limited resources; students' motivation and independent learning skills differ on the basis of their socioeconomic status; and the issues of mind wandering and concentration, which manifest in various ways. Despite school resumption, these findings show that the negative impacts remain in today's classrooms. This research argues that the negative consequences differentially affect students and proposes the need to coin the term ‘pandemic digital structural violence’ (PDSV) to address the core problem accurately. This research urges educators to be aware of PDSV and avoid blaming their students. It also urges policy makers to address the unfairness while moving on to develop digitised education further.
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 | 0.001 | 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 | 0.000 |
| 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 it