Professionalism and the Construction of Teacher Professional Identity
Bibliographic record
Abstract
Professionalism and the construction of teacher professional identity is a focus of our teacher education program and a pillar that guides the daily practices of educators (OCT, 2016). For teachers to be viewed as professionals within their classroom and community, they must understand the high standards of being a teacher and strive every day to meet and exceed those expectations (Hurst & Reading, 1999). The purpose of our collaborative research is to explore how teachers determine the fine line between professionalism and compassion in the classroom and in professional relationships. The findings suggest that professional relationships are constantly evolving and that boundaries are of utmost importance for teachers. Educators must follow professional standards while maintaining a balance between compassionate support and professional impartiality regarding student’s needs. The root of professionalism is effective multilateral communication between teachers, administration, parents, and students. A multi-faceted understanding of professionalism is essential for new teacher candidates to ensure their professional success and the effective learning of students in the classroom. These recommendations will help teacher candidates and new educators maintain professional relationships and evaluate their conduct within the educational community.
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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.015 | 0.047 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".