Breaking solitudes: identity, motivation and investment in a group of adult language learners
Bibliographic record
Abstract
Breaking solitudes and claiming the right to speak AKNOWLEDGEMENTS It is with great pleasure that I dedicate these few words of thanks to the numerous people who helped me complete this great peregrination.Firstly, I would like to thank my supervisor Roy Lyster for his belief in my ideas, his acute critical sense, his vast knowledge, and for the indispensable guidance he has given me throughout this process.And to Mela Sarkar, whose harsh but warranted critique of my initial effort helped me to clarify my conceptual lens.Secondly, my undying appreciation goes to the two most important people in my life, my wife Livia Royea and my mother Julia Dawson.My wife for her patience, unconditional love and delicious food to fuel my body, mind, and soul.My mother for having brought me into the world and for giving me the means to stay firmly on it.In addition, I thank my mother for her much appreciated organizational help and assistance with the lengthy task of transcription.My thanks also go out to other members of my family and friends who
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".