Bibliographic record
Abstract
It was natural for us to work together as co-editors because we had worked together on various exchange programs between our two universities, and because Chuntian had published in our Journal (Chen & Zhang, 1998, TCJ, 15(2), pp.69-74) and served on the Review Board for volumes 18, 19, and 20.Professionalism is a complex construct, yet there is very little academic literature on it.The Canadian Oxford Dictionary (1998) defines professionalism as "the skill or qualities required or expected of members of a profession."A profession is a "vocation or calling, esp.one that involves some branch of advanced learning or science (the medical profession)."This Special Issue presents six full-length articles directly or indirectly focusing on one or more aspects of professionalism.In the first article, MacPherson, Turner, Khan, Hingley, Tigchelaar, and Dustan Lafond exercise their professional responsibilities as members of TESL Manitoba and TEAM (the two ESL teacher organizations in Manitoba) by collaborating to write a background article for Manitoba's diversity and equity policies.They propose their findings as a "mandate for the development of our field in Canada."In the second article, Breshears examines the position of ESL teachers on the spectrum between unskilled workers and highly trained professionals.She considers features of established professions and calls for "further empirical research into the working conditions of English language teachers."Article three provides some of that empirical research.Thomson proposes "basic requirements that should be expected of any professionally adequate TESL training program."He then assesses 10 programs from across Canada by these professional standards and makes recommendations for TESL Canada in its work on setting national standards.Fleming and Walter, in article four, address an important characteristic of professionalism: autonomy.They propose "an experiential learning approach ... to help counter the trend [of] teachers ... losing professional autonomy."In article five, Deckert proposes and illustrates "five guidelines for ethical selection of lesson topics."These guidelines will be of great help for ESL curriculum developers and classroom teachers in their professional responsibilities to their students.
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 | 0.003 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.105 | 0.079 |
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".