Bibliographic record
Abstract
Business English for Success is a creative solution to a common challenge across Business Communication courses: Business English or Business Presentations? Some classes place an equal emphasis on oral and written communication. If that’s the case for you check out our text Business Communication for Success. If, however, your class places the emphasis squarely on written communication and writing proficiency, then Business English for Success is for you. Business English for Success provides instruction in steps, builds writing, reading and critical thinking, and combines comprehensive grammar review with an introduction to paragraph writing and composition. This step-by-step approach provides a clear path to student-centered learning. A wide range of writing levels and abilities are addressed, helping each student prepare for the next writing or university course. The text opens with a discussion on the sentence and then breaks it down into its elemental components, before reconstructing them into effective sentences, paragraphs and larger assignments. Then, starting in Chapter 9: Effective Business Writing, the discussion applies lessons learned from the previous foundational chapters into common business issues and applications. From paraphrasing and plagiarism to style to the research process, the expectations increase as several common business documents are presented, including text messages and e-mail, memorandums and letters, the business proposal, business report, resume and the sales message. This textbook has been used in classes at: Arizona Western College, Hostos Community College, Virginia State University, Truckee Meadows Community College, San Jose State University, Concordia University - Irvine, University New Brunswick - Fredericton, Cerritos College, University of Houston - Downtown, Flat World Knowledge University, A-C Central High School, University of The People, Truckee Meadows Community College, Danville Community High School
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.160 | 0.101 |
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".