Shadow ESL Education from North American Tutors’ Perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
For-profit, private tutoring services, often referred to as shadow education, are tutoring students for pay and are made use of as a concurrent supplement to their standard academic courses or programs. These tutoring sessions are often online and given by tutors who work for companies that are for-profit businesses in the education services industry. Tutors are often subject matter “experts” working as independent contractors, many of whom have little or no formal training as teachers. This is a qualitative case pilot study consisting of semistructured interviews with two such tutors working at a company that offers online tutoring in content areas and ESL to Chinese international undergraduate students studying abroad in Canada, the US, Australia, and the UK. Data reveal that these tutors have concerns with their sense of professional identity as teachers. These results elicit questions of who has the privilege of being called a “teacher” and the status of online for-profit tutors as compared to classroom teachers. Findings also include that tutors’ perceptions of working for a for-profit shadow education company impacts their teaching practices.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it