<scp>Jacqueline Lindenfeld</scp>, <i>The French in the United States: An ethnographic study</i>. Westport, Conn.: Bergin & Garvey, 2000. Pp. xiv + 184. Hb $55.00.
Bibliographic record
Abstract
The French in the United States offers valuable insight on processes of identity formation among French-born individuals living permanently in the US. The book's title foreshadows the ambiguity of how the French in America are defined in objective terms, as well as their subject positioning as members of an ethnic group. For instance, Lindenfeld cautions against relying on the criterion of ancestry used in census-based rankings to study the French presence in the United States, since census identification includes people of various national origins and does not distinguish the number of intervening generations since departure from France. The limitations of the native use of the French language as a valid indicator of direct French origin neglects the fact that native speakers of French who reside in the US often possess Canadian or Caribbean lineage. Although Lindenfeld does not say so directly, relying on native use of French to identify direct immigrants from France would equally exclude the possibility of identifying French citizens who do not speak French as their first language, as well as those who were raised speaking two or more languages. Another concern raised in the book is the broad significance of the label “French American,” traditionally used to identify Americans of French ancestry, such as Cajuns in Louisiana. The designation currently enjoys a certain popularity among French immigrants because it offers a direct parallel with other immigrant groups, such as Italian Americans.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 0.007 |
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".