Between the Test and the Deep Blue Sea: Sneaking Anthropology into the Classroom in Post- “No Child Left Behind” America
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Since the implementation of the No Child Left Behind Act of 2001 (2002), K-12 teachers in the United States (US) have operated under a legal regime of standardised testing, designed to measure student progress on pre-determined metrics. However, many teachers, and their students, find this approach stifling and inconsistent with the student-centred, Freirean liberation pedagogy approach they often encounter in teacher training programmes. This piece looks at the tension between educational policy and teaching philosophy. Through my own experiences as a high school social studies teacher in the US, I demonstrate how I used ethnographic methods in my classroom to foster an anthropological sensibility. I focus on one specific project – the Snapshot Migration Story – and how I used it to carve a space for ethnographic exploration, student-centred curriculum, and project-based learning. This anthropological sensibility provided “windows and mirrors” to the students, helped “make the familiar strange and the strange familiar,” and helped students navigate an educational landscape that tried to both create lifelong, passionate learners, as well as students with the ability to reliably and consistently pass standardised tests.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.015 | 0.047 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it