Professional capital after the pandemic: revisiting and revising classic understandings of teachers' work
Bibliographic record
Abstract
Purpose This article revisits three classic findings from Dan Lortie's 1975 book Schoolteacher, in the context of the coronavirus pandemic and its possible aftermaths. These findings are that teachers and others base their ideas about teaching on the long apprenticeship of observation as students; they derive their satisfaction from the psychic rewards of teaching – the emotional satisfaction and feedback that teachers got from students; and they work in conservative cultures of individualism. Design/methodology/approach The article appraises Lortie's foundational text in relation to contemporary public domain surveys and op-ed articles about the impact of the pandemic on teaching and learning. Findings COVID-19 created conditions that undermined traditional psychic rewards, weakened the tenuous student–teacher relationship as more students found schooling less engaging, began to give parents distorted observations of teaching online and made teacher collaboration more difficult. Research limitations/implications Due to the current nature of the pandemic and the shortage of just-in-time original data, the research relies on rapid responses and op-ed perceptions rather than on an established body of literature and database. Practical implications The postpandemic agenda holds out three ways to modernize Lortie's agenda in ways that advance the presence and impact of professional capital. These ways comprise new psychic rewards for students and not just teachers, a more open professionalism that is actively inclusive of parents and collaborative professionalism that has greater strength and depth. Social implications Educational reform in the postpandemic age must be transformational and not seek to return to normal. Originality/value The paper gives new meaning to Lortie's original ideas on COVID-19 circumstances
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 | 0.015 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.008 | 0.090 |
| Scholarly communication | 0.016 | 0.021 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".