Where Do I Belong in the United States Public School System?
Bibliographic record
Abstract
I seek to inquire about the world as it relates to my identity as a first generation descent of the Penobscot tribe living in the United States by utilizing four methodologies in my research: life histories/autobiographies, narrative inquiry, a/r/tography and practice-based and practice-led. Through coupling my artistic practice with those four methodologies I am able to creatively show the information I have unearthed in hopes that others will benefit from a fresh and augmented understanding of what it historically and culturally means to be a part of a community that makes up a very small percentage of the United States demographic: the Native Americans, or what I prefer to call the Indigenous peoples/Indigenous peoples of North America. This thesis explores the intersections between growing up within Western European and North American Indigenous culture and education. By analyzing how a person determines their identity through their experiences with home environment, society, and the education system, this thesis document will examine the challenges that come from expressing and understanding race and identity as a North American Indigenous person. In this document, I am looking to scholars in the fields of indigenous studies, anthropology, sociology, and other disciplines of the humanities. I am looking to cross-examine the content that the United States education system provides surrounding the history and portrayal of Native Nations. There are currently more and more discrepancies being brought to light by indigenous studies scholars, and Native Nations documenting their true histories that are not mentioned in textbooks that are handed out to students in United States public schools. It is the exploration of the interconnections of being a woman, artist, educator, and native person that drives the research and creation of my art practice. Through creating art related to societal problems I hope to promote awareness where we can learn from our past mistakes and facilitate a dialogue where people can talk about what we can do to improve society for future generations.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".