Bibliographic record
Abstract
The Indigenous people of the Arctic refer to themselves as "Inuit" (people)."Eskimo" is no longer used in Canada.I have sparingly used the word "Eskimo" in historical quotations or where the context makes it appropriate.There are several good dictionaries of Inuktitut in print, as well as websites dedicated to teaching Inuktitut on the Internet.I have listed one of each in the Bibliography.In addition, many books on the Arctic include useful glossaries, including Uqalurait: An Oral History of Nunavut, edited by John Bennett and Susan Rowley.I recommend this book to anyone who is interested in Inuit oral history and culture.Whenever I have used an Inuktitut word or phrase for the first time, I have provided a translation.Inuktitut is spoken in several dialects, some of which are reflected in the spelling of different words used in this book.Inuktitut from older sources (such as in Knud Rasmussen's writings) is reproduced with the original English spelling, although much of this is now archaic.My knowledge of Inuktitut is limited, so I have been fortunate in having fluent speakers and writers to help me over the years, including Susan Enuaraq, John Houston, Sandra Inutiq, Piita Irniq, Elisapee Karetak, Alexina Kublu, Mick Mallon, Aaju Peter, Paul Quassa, and Lucien Ukaliannuk.Whatever errors there are (and I'm sure there are some) are entirely my own responsibility.
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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.179 | 0.196 |
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".