Bibliographic record
Abstract
07–430Anson, Chris M. (N Carolina State U, Raleigh, USA; chris_anson@ncsu.edu ), Assessing writing in cross-curricular programs: Determining the locus of activity. Assessing Writing (Elsevier) 11.2 (2006), 100–112. 07–431Chanock, Kate (La Trobe U, Bundoora, Australia; c.chanock@latrobe.edu.au ), Help for a dyslexic learner from an unlikely source: The study of Ancient Greek. Literacy (Oxford University Press) 40.3 (2006), 164–170. 07–432Cole, Simon (Daito Bunka U, Japan), Consciousness-raising and task-based learning in writing. The Language Teacher (Japan Association for Language Teaching) 31.1 (2007), 3–8. 07–433Daniels, Peter T. (New Jersey, USA). On beyond alphabets. Written Language and Literacy (Benjamins) 9.1 (2006), 7–24. 07–434Dovey, Teresa (U Technology, Sydney, Australia), What purposes, specifically? Re-thinking purposes and specificity in the context of the ‘new vocationalism’. English for Specific Purposes (Elsevier) 25.4 (2006), 387–402. 07–435Dowdall, Clare (U Plymouth, UK; c.dowdall@plymouth.ac.uk ), Dissonance between the digitally created words of school and home. Literacy (Oxford University Press) 40.3 (2006), 153–163. 07–436Elbow, Peter (U Massachusetts, Amherst, USA; elbow@english.umass.edu ), Do we need a single standard of value for institutional assessment? An essay response to Asao Inoue's ‘community-based assessment pedagogy’. Assessing Writing (Elsevier) 11.2 (2006), 81–99. 07–437Green, Anthony (U Cambridge, ESOL Examinations, Cambridge, UK; Green.A@cambridgeesol.org ), Washback to the learner: Learner and teacher perspectives on IELTS preparation course expectations and outcomes. Assessing Writing (Elsevier) 11.2 (2006), 113–134. 07–438Holme, Randal & Bussabamintra Chalauisaeng (Hong Kong Institute of Education, Hong Kong, China), The learner as needs analyst: The use of participatory appraisal in the EAP reading classroom. English for Specific Purposes (Elsevier) 25.4 (2006), 403–419. 07–439Jia, Yueming Zohreh R. Eslami, & Lynn M. Burlbaw (Texas A & M U, USA), ESL teachers' perceptions and factors influencing their use of classroom-based reading assessment. Bilingual Research Journal (National Association for Bilingual Education) 30.2 (2006), 407–430. 07–440Kirkgöz, Yasemin (Çukurova U, Turkey; ykirkgoz@cu.edu.tr ), Designing a corpus based English reading course for academic purposes. The Reading Matrix (Readingmatrix.com) 6.3 (2006), 281–298. 07–441Lambirth, Andrew (Canterbury Christ Church U, UK; al4@cant.ac.uk ) & Kathy Goouch, Golden times of writing: The creative compliance of writing journals. Literacy (Blackwell) 40.3 (2006), 146–152. 07–442Li, Yongyan (City Hong Kong, China), A doctoral student of physics writing for publication: A sociopolitically-oriented case study. English for Specific Purposes (Elsevier) 25.4 (2006), 456–478. 07–443Moreira, Sylvia (City U New York, USA) & Maryellen Hamilton. Goats don't wear coats: An examination of semantic interference in rhyming assessments of reading readiness for English language learners. Bilingual Research Journal (National Association for Bilingual Education) 30.2 (2006), 547–557. 07–444Penney, Catherine (U Newfoundland, Canada) James Drover, Carrie Dyck & Amanda Squires, Phoneme awareness is not a prerequisite for learning to read. Written Language and Literacy (Benjamins) 9.1 (2006), 115–133. 07–445Serniclaes, Willy (U René Descartes, Paris, France), Allophonic perception in developmental dyslexia: Origin, reliability and implications of the categorical perception deficit. Written Language and Literacy (Benjamins) 9.1 (2006), 135–152. 07–446Suzuki, Akio (Josai U, Japan), Differences in reading strategies employed by students constructing graphic organizers and students producing summaries in EFL reading. JALT Journal (Japan Association for Language Teaching) 28.2 (2006), 177–196. 07–447Stapleton, Paul (Hokkaido U, Sapporo, Japan) & Rena Helms-Park, Evaluating Web sources in an EAP course: Introducing a multi-trait instrument for feedback and assessment. English for Specific Purposes (Elsevier) 25.4 (2006), 438–455. 07–448Zhu, Yunxia (U Queensland, New Zealand; zyunxia@unitec.ac.nz ), Understanding sociocognitive space of written discourse: Implications for teaching business writing to Chinese students. International Review of Applied Linguistics in Language Teaching (Walter de Gruyter) 44.3 (2006), 265–285.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.740 | 0.743 |
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".