In the Community: An Intermediate Integrated Skills Textbook
Bibliographic record
Abstract
An Intermediate Integrated Skills Textbook!This textbook is an English language learning textbook.It will help you notice, learn, and practice English that will be helpful in your community.The textbook • gives you practice in the four main language skills-listening, speaking, reading, and writing • helps you learn about intercultural skills • helps you develop some important essential skills • is an Open Educational Resource (OER) that can be used in two different ways.You can use it as an online textbook with interactive activities, or you can download it, print it and use it as a regular textbook.You will meet the following people in the textbook.Note to the Learner | 3 1.Reading Before You Read Complete these pre-reading activities to help you recognize formality and distance, and to understand conversations better. Formal and Informal Ways of TalkingIn Focus Questions 1 and 2, you filled in tables.Tables are a type of form that controls what we write and how much we write.When we communicate formally, we have to control the words we use to be polite or well organized.In formal speech, we also control how fast we speak and how carefully we pronounce words.Decide how formal the following communication styles are.When Roshan and Kerry are sitting in the coffee shop, Kerry said, "C'mon.You've gotta be kidding me.What the heck is going on?Look at all those cars.They're at a stand still.We're gonna be late.Darn construction…" When Roshan and Nick were talking, Roshan said, "Hey Nick… See ya."When Gilles phoned Claire, he said, "Am I speaking with Mrs. Turner?Good morning… It's Gilles Doucette here."Place for Kerry, for Nick,
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.102 | 0.042 |
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".