From Despair to Hope: A Narrative Journey to Becoming Amateur Intellectuals During COVID-19
Bibliographic record
Abstract
In this narrative paper, we explore our coming-of-age as amateur intellectuals through our collaborative engagement with reflexivity during the COVID-19 pandemic. Situating our reflective acts within technology and our educational contexts we address and analyze feelings of persistent tug of war between despair and hope. Through collaborative autoethnography, we challenged our perceptions and investigated our views on educator identity as “teachers” to challenge perceptions of educator roles and responsibilities. We discuss how the COVID-19 pandemic response narrowed the role of the teacher, ultimately diminishing and destabilizing teacher identity while limiting their sense of agency. We draw on our collective experiences during the pandemic to draw a thread between the pandemic response’s effect on teaching and teacher identity, a conflicting awareness of both complicity and resistance, and our battles with the despair of necessity. By engaging in collaborative doubt and reflexivity, we discovered that we were consistently instilled with an astonishing sense of hope within our community.
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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 | 0.015 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.047 | 0.062 |
| Scholarly communication | 0.020 | 0.016 |
| Open science | 0.003 | 0.027 |
| Research integrity | 0.007 | 0.017 |
| Insufficient payload (model declined to judge) | 0.004 | 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".