THE PERSISTENCE OF TRADITIONAL VALUES: GRANDPARENTS REARING GRANDCHILDREN
Bibliographic record
Abstract
Abstract The goal of this study is to examine how cultural values are preserved and transmitted by grandparents rearing grandchildren in one community in the southeast region of the Yukon-Koyukuk Census Area in Alaska. The eight participants (six females and two males) lived in a community in the Kusilvak Census Area, with ages ranging from 47 to 73 years old. Participants’ took part in a semi-structured interview, which were then transcribed and coded into larger themes of 1) loss of traditional values, 2) continuing traditional values, 3) practicing traditional values, and 4) transmitting traditional values. The participants provided examples of how the cultural values that were strong at one point in their lives, were no longer exemplified in their community, and, in fact, behaviors that went against accepted values were seen. Participants spoke most often of how community members were cared for, how the community was valued over the individual, and the connections within families. The GRGs practiced those traditional values by caring, supporting, and loving the people in their families and communities, and by practicing humor and sharing with others. While this community has been influenced by modern ways of living currently found in the United States and Canada, it still remains relatively isolated from the technological and social influences that dominate what is considered “typical, modern” family life. The findings from this study illustrate the important roles that GRGs play in the persistence of cultural values, and the importance of incorporating these values in programs to assist this community.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".