Bibliographic record
Abstract
While conducting a qualitative, semi-structured interview study that investigated the role of program administrators and managers in the field of teaching English to speakers of other languages (TESOL), the author encountered a TESOL professional whose 30-year career as an instructor, administrator, and owner of her own language school was so inspirational as to warrant its own exploration as a continuous professional development case study. Using the conceptual framework of continuous professional development (CPD) through the lenses of critically reflective practice and transformative and transformational learning (Brookfield, 2017; Cranton, 1996; Freire, 2007; Mezirow, 1991) and the methodological framework of the use of narratives in TESOL and teachers’ narrative inquiry as professional development (Johnson & Golombek, 2002; Pavlenko, 2002), the author unravels each step of Sophie’s career as a guidebook for other TESOL professionals who might be contemplating a similar journey. The author’s findings highlight the impetus and decision-making processes behind each transition in her career trajectory and concludes by illuminating what Sophie identified as lessons learned. Since many TESOL professionals aspire to open their own language schools in an English as a foreign language (EFL) context, the lessons learned from that enterprise were delineated separately. The critical roles preservice preparation, CPD, and effective supervision and mentorship play when transitioning into administrative positions were identified as areas for further investigation and research, including how modifications in these areas might foster a more seamless professional evolution into entrepreneurship.
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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.034 | 0.011 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.004 | 0.013 |
| Insufficient payload (model declined to judge) | 0.005 | 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".