Educating for advanced foreign language capacities : constructs, curriculum, instruction, assessment
Bibliographic record
Abstract
Figures and Tables Preface 1. Locating the Advanced Learner in Theory, Research, and Educational Practice: An IntroductionHeidi Byrnes, Georgetown University Part I: Cognitive Approaches to Advanced Language Learning 2. The Conceptual Basis of Grammatical StructureRonald W. Langacker, The University of California, San Diego 3. The Impact of Grammatical Temporal Categories on Ultimate Attainment in L2 LearningChristiane von Stutterheim and Mary Carroll, University of Heidelberg 4. Reorganizing Principles of Information Structure in Advanced L2s: French and German Learners of EnglishMary Caroll and Monique Lambert, University of Heidelberg and University of Paris VIII 5. Language-based Processing in Advanced L2 Production and Translation: An Exploratory StudyBergljot Behrens, Department of Linguistics and Nordic Studies, University of Oslo 6. Learning and Teaching Grammar through Patterns of Conceptualization: The Case of (Advanced) KoreanSusan Strauss, The Pennsylvania State University and Center for Advanced Language Proficiency Education and Research (CALPER) Part II: Descriptive and Instructional Considerations in Advanced Learning 7. Narrative Competence in a Second LanguageAneta Pavlenko, Temple University and Center for Advanced Language Proficiency Education and Research (CALPER) 8. Lexical Inferencing in L1 and L2: Implications for Vocabulary Instruction and Learning at Advanced LevelsT. Sima Paribakht and Marjorie Wesche, University of Ottawa 9. From Sports to the EU Economy: Integrating Curricula through Genre-based Content CoursesSusanne Rinner and Astrid Weigert, Georgetown University 10. Hedging and Boosting in Advanced-Level L2 Legal Writing: The Effect of Instruction and FeedbackRebekha Abbuhl, California State University at Long Beach Part III: The Role of Assessment in Advanced Learning 11. Assessing Advanced Foreign Language Learning and Learners: From Measurement Constructs to Educational UsesJohn M. Norris, University of Hawai'i at Manoa 12. Rethinking Assessment for Advanced Language ProficiencyElana Shohamy, Tel Aviv University
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.083 | 0.021 |
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".