Bibliographic record
Abstract
04–198Chandler-Olcott, Kelly and Mahar, Donna (Syracuse U., USA; Email: kpchandl@syr.edu ). ‘Tech-savviness’ meets multiliteracies: exploring adolescent girls' technology-mediated literacy practices. Reading Research Quarterly (Newark, USA), 38, 3 (2003), 356–85. 04–199Chung, Teresa Mihwa & Nation, Paul (Victoria U., New Zealand; Email: Paul.Nation@vuw.ac.nz ). Identifying technical vocabulary. System (Oxford, UK), 32, 2 (2004), 251–63. 04–200Ellis, Rod and Yuan, Fangyuan (U. of Auckland, New Zealand; Email: r.ellis@auckland.ac.nz ). The effects of planning on fluency, complexity, and accuracy in L2 narrative writing. Studies in Second Language Acquisition (New York, USA) 26, 1 (2004), 59–84. 04–201Gascoigne, Carolyn (U. of Nebraska-Omaha, USA). Examining the effect of feedback in beginning L2 composition. Foreign Language Annals (New York, USA), 37, 1 (2004) 71–76. 04–202Hamston, J. and Love, K. Reading relationships: Parents, boys, and reading as cultural practice. Australian Journal of Language and Literacy (Adelaide, Australia), 26, 3 (2003), 44–57. 04–203Hobbs, Renee and Frost, Richard (Babson College, USA). Measuring the acquisition of media-literacy skills. Reading Research Quarterly (Newark, USA), 38, 3 (2003), 330–55. 04–204Huang, Jingzi (Monmouth University, USA; Email: jhuang@Monmouth.edu ). Socialising ESL students into the discourse of school science through academic writing. Language and Education (Clevedon, UK), 18, 2 (2004), 97–123. 04–205Johnston, Brenda (U. of Southampton, UK; Email: bhm@soton.ac.uk ). Teaching and researching critical academic writing: scrutiny of an action research process. Educational Action Research (Oxford, UK), 11, 3 (2003), 365–87. 04–206Kamler, B. (Deakin University, Australia). Relocating the writer's voice – from voice to story and beyond. English in Australia (Norwood, Australia), 138 (2003), 34–40. 04–207Kim, Hae-Ri (Kyungil U., South Korea; Email: hrkimasu@hanmail.net ). Dialogue journal writing through a literature-based approach in an EFL setting. English Teaching (Anseonggun, South Korea), 58, 4 (2003), 293–318. 04–208Kim, Myonghee (Indiana University, USA; Email: mahn@indiana.edu ). Literature discussions in adult L2 learning. Language and Education (Clevedon, UK), 18, 2 (2004), 145–66. 04–209Lee, Icy (Hong Kong Baptist U., Hong Kong; Email: icylee@hkbu.edu.hk ). L2 writing teachers' perspectives, practices and problems regarding error feedback. Assessing Writing (New York, USA), 8, 3 (2003), 216–37. 04–210Lindgren, Eva (Email: eva.lindgren@engelska.umu.se ) and Sullivan, Kirk P. H. Stimulated recall as a trigger for increasing noticing and language awareness in the L2 writing classroom: a case study of two young female writers. Language Awareness (Clevedon, UK), 12, 3&4 (2003), 172–86. 04–211Luke, A. (U. of Queensland, Australia/National Institute of Education, Singapore). Making literacy policy and practice with a difference. Australian Journal of Language and Literacy. (Adelaide, Australia), 26, 3 (2003), 58–82. 04–212Mission, R. (U. of Melbourne, Australia). Imagining the self: the individual imagination in the English classroom. English in Australia (Norwood, Australia) 138 (2003), 24–33. 04–213Morris, Darrell, Bloodgood, Janet W., Lomax, Richard G. and Perney, Jan (Appalachian State U., USA). Developmental steps in learning to read: a longitudinal study in kindergarten and first grade. Reading Research Quarterly (Newark, USA), 38, 3 (2003), 302–28. 04–214Ryu, Hoyeol (Hankyong National University, Korea; Email: hoyeol@hnu.hankyong.ac.kr ). Process approach to writing in the post-process era: A case study of two college students' writing processes. English Teaching (Anseonggun, Korea), 58, 3 (2003), 123–42. 04–215Shen, Helen H. (University of Iowa, USA; Email: Helen-shen@uiowa.edu ). Level of cognitive processing: effects on character learning among non-native learners of Chinese as a foreign language. Language and Education (Clevedon, UK), 18, 2 (2004), 167–82. 04–216Shi, Ling (U. of British Columbia, Canada). Textual borrowing in second-language writing. Written Communication (Thousand Oaks, California, USA), 21, 2 (2004), 171–200. 04–217Spence, Lucy K. (Arizona State University, USA). Stepping out of the conversation: giving students a space to co-construct writing. Bilingual Research Journal (Arizona, USA), 27, 3 (2003), 523–32.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.234 | 0.139 |
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".