Bibliographic record
Abstract
A lightening rod for an array of criticism, Coming of Age in Samoa also attained monumental popularity with both scholarly and popular reading audiences, convincing many that it captured the sexual and social lives of Samoan adolescent girls and that North American girls might be instructed by this portrait. Taking a “recovery and reappraisal” approach, this article argues that the text is neither a collection of detailed, field note-anchored observations nor a cross cultural critique, but a love story to place. The text has much in common with postmodern conceptions of ethnography, which acknowledge “writing culture” as mediated by interpretive, representational and linguistic considerations. Like many postmodern ethnographers, Mead self-consciously constructs an authorial position rather than attempting to remain absent and objective. Part of the persona she constructs is that she is a scientist sharing data; yet she no sooner invokes standards of scientific rigor than she shifts course to promise us a good “tale”. If contemporary readers can read the text through a postmodern lens, when she wrote, her approach was unprecedented. Her awareness of transgressing scientific method emerges in the “Introduction” to the book, where she self-reflects on her decisions about authorship as performance and text as storied, artful and intimate.
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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.027 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".