Internet-Based Cultural Enrichment in the Polish Language Classroom
Bibliographic record
Abstract
Most introductory and intermediate textbooks for Polish, currently in use, are written in Poland and intended for intensive language study in-country where the “little-c” cultural component is inherent and immediate in an intensive language program. One of the most widely used textbooks in North America is the series, Hurra!!! po polsku I, II, III. This textbook is based on a communicative approach to language pedagogy and consists of thematic chapters according to aspects of life and culture in everyday society. The intent of the Hurra!!! po polsku series is that students will experience Poland while learning the language. This presents a problem to educators of Polish in the United States. Numerous communicative exercises presuppose acquaintance with the target culture while providing little in the way of input. We have found that students have difficulty relating to many exercises that carry specific cultural information. Our project is based on two specific goals: first, to decrease the amount of time spent in class to explain culture-specific aspects of the textbook; and second, to spare our students at least some amount of the usual culture shock one experiences when traveling to Poland. In this report, we describe a website, exercises, and activities we developed to accompany the textbook.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".