The Emotional Toll of Obligation and Teachers’ Disengagement from the Profession
Bibliographic record
Abstract
Patricia" is a former teaching colleague and an experienced grade one teacher."Devan" is one of her students.Frequently violent and uncontrollable, Devan has to be physically restrained until calm.In such moments, Patricia calls the office to send help.No one ever comes.Feeling shaken after each of these episodes, she worries about her distressed relationship with Devan, and about what the other children think when they witness such scenes.She worries about the safety of the students, the lack of support for Devan's family, how the other teachers and the principal judge her, and the curriculum that is not being taught.One afternoon, Patricia is rushed to hospital with chest pains.The diagnosis: badly bruised ribs, the result of Devan's head banging against her chest while being restrained.The prognosis: immediate stress leave, followed by Patricia's decision to leave the profession altogether.When asked about her motives for leaving, Patricia simply cites "job dissatisfaction."Devan and his classmates finish the year with an array of substitute teachers.This true story illustrates how obligation, or the binding responsibility to respond to the other, both lends teaching its moral integrity, but also takes an enormous emotional toll on those who teach.Obligation is of particular importance today given that education is increasingly being restructured by ideologies of the market and managerialism that seek to minimize the moral integrity of teaching, and invoke feelings of self-doubt, guilt, anxiety, and shame in teachers (Ball, 2003).The effect is teacher burnout and greater attrition that negatively impact students (Crocco & Costigan, 2007).Our purpose in this two-year inquiry is to illustrate and explore how teachers experience and understand obligation; to unravel the complex relation between the emotional toll of obligation and teachers' disengagement in all its forms; and finally, to closely examine the profession's understanding and response to the anxiety of obligation.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.028 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.004 | 0.016 |
| 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".