Performing Identities as Literate Fourth Graders via (D)iscourse in a Testing-Driven Classroom
Bibliographic record
Abstract
Students in every classroom construct a (D)iscourse of literacy that reflects not only who they are but their environment as well. (D)iscourses are more than just dialogues, rather they integrate not only the cultural values and norms of that situation, but also the specific language needs (Gee, 2001). Additionally, (D)iscourses reveal the internal narratives of individuals as they present themselves within context to others (Bruner, 2002). The No Child Left Behind Act of 2001 (NCLB) introduced new influences on school and classroom environments. NCLB implemented standardized, high-stakes testing to measure student, teacher and school performance, attaching serious consequences to not meeting appropriate norms (Allington & McGill-Frazen, 2004). Thus the tests, and the need for specific results, frequently influenced classroom practices (Valencia & Wixson, 2004). This research explored these influences upon students? (D)iscourses during classroom literacy events through three research questions: (1) What are fourth-graders? (D)iscourses of literacy in a standards-based/testing driven world? (2) What or whom mediates those (D)iscourses? (3) What do the (D)iscourses reveal about the fourth-graders? developing identities as literacy learners? Data sources included classroom observations by the researcher, audiotaped classroom dialogues, participant student and teacher interviews, as well as student artifacts. Constant comparative analysis (Glaser & Strauss, 1967) viewed through the lens of critical literacy theory (Giroux, 1990) was used to analyze the data. Methodological rigor was established using the criteria of trustworthiness (Lincoln & Guba, 1985). The students? (D)iscourse was found to be personal, pragmatic and particular. It was mediated principally by their teacher through her role as the filter of knowledge in the classroom. Her role as filter shifted with different classroom requirements (such as standardized testing) to become a project manager, a coach/trainer and a gatekeeper. The students were found to have detached themselves from school literacy, developing self-reliant or ambivalent stances toward literacy. These results illustrate the collision between traditional and progressive philosophies in many schools today.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".