Bibliographic record
Abstract
This paper reflects upon my experiences teaching and learning from displaced youth in Greece over a period of eight months in 2017. Following a brief examination of the current challenges in accessing formal education, I examine non-formal education initiatives, summarizing my work with two NGOs in Athens and Chios where I taught lessons in English on ancient Greek art, archaeology, history, and literature. In offering these lessons, my hope was to do more than simply improve students’ language skills or deposit information: I wanted to examine the past to reflect upon the present, exploring themes of migration, forced displacement, and human belonging. Moreover, I wanted to engage students in meaningful connection, to the past and to the present, to one and to others, as a means of building community in and beyond the classroom, at a time when many were feeling alienated and isolated. This paper, therefore, outlines the transformational, liberating learning that took place, citing ancient evidence of displacement and unpacking modern responses by those currently displaced.
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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.022 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.005 | 0.027 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".