Higher Education’s Marketization Impact on EFL Instructor Moral Stress, Identity, and Agency
Bibliographic record
Abstract
Higher educational institutions (HEIs) have experienced a dramatic reconceptualization as academia strives to align its organizational design and civic mission with the societal notion that education is obliged to prioritize quantifiable results. The traditionalistic ethos that knowledge is acquired through reason and the pursuit of critical inquiry has been supplanted by a marketized ideology that education is a transactional process. The latter notion fails to foster the development of students’ core competencies. The resulting commodification of education has repurposed HEIs from serving a public good to serving a private good and has impacted institutional policies, program offerings, curriculum design, pedagogy, and instructor and student assessment. English foreign language (EFL) programs face immense pressure to conform to external idealized beliefs concerning appropriate course design and implementation. Such pressure limits instructors’ ability to perform their tasks efficiently. The burden of cultural and institutional constraints and unmanageable expectations has led to myriads of professional and moral stresses that negatively affect EFL instructors’ identity and agency in their occupation. This article explores the marketization of universities and its subsequent impact on EFL instructors. Demands from various stakeholders create moral stress for instructors; influence instructor identity through shaping the perceived, actual, and external ought self; and produce damaging consequences related to diminished instructor agency in the classroom.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".