Bibliographic record
Abstract
BACKGROUNDFor most people, informal networks of family and friends provide die ties along which social, emotional, instrumental, material, and financial assistance is exchanged. For many with scant resources, informal exchange is key in enabling survival (e.g., Stack, 1974; Zavella, 1987). Even for tiiose with more resources, this support provides connection and aid at life transitions, such as while establishing one's self in young adulthood (e.g., Logan & Spitze, 1996) or becoming more dependent in later life (Connidis, 2001). Another important life transition is marriage. Those who are married can differ significantly from those who are single in the types of aid that are both needed and available. This report explores such possibilities, examining how support exchange is related to the marital status of those involved, and how that may differ by gender. The data are from a survey on support exchange conducted by the author.PRIOR RESEARCH ONMARRIAGE AND SUPPORT NETWORK PARTICIPATIONPrior research demonstrates a number of differences in support network exchange which are related to the marital status of the participants. The social networks of the married are larger than those of the unmarried (Rands, 1988). The married are more prone to give monetary aid to network members than are the unmarried. Coresidence of adult children and parents is more prevalent if the adult children are single (Aquilino, 1990). Unmarried people are likely to give aid requiring time rather than money, such as rides or help with chores (Rossi & Rossi, 1990). Almeida et al. (2001) noted that single men and women give fewer dollars per week to their kin than do married men and women. Marital status also affects aid received. Adult children give more assistance to parents who are single than to parents who are married (Coward etal., 1992).Marital status hence corresponds to a variety of differences in support networks. It also is a truism that men and women exchange aid differently. Johnson (2000) found that women are more involved with their relatives than are men, contacting them more frequently and giving and receiving more help. Women exchange different types of aid with family and friends than do men, with the type of help often corresponding to gender norms (Rossi & Rossi, 1990). For example, women provide emotional support to members of their network (Wellman & Wortley, 1990) and men use their job skills to help each other (Wellman, Carrington, & Hall, 1988).Prior work thus suggests that both marital status and gender correspond to different types of exchanges between various support network members. This report examines how marital status and gender are intertwined in shaping the types of exchange people give each other. It does so using a sample selected to maximize its racial/ethnic diversity, whereas much of the research cited above is based upon primarily White samples.RESEARCH SITE, METHODS AND SAMPLEThis paper is based on fieldwork conducted in Culver City, California between 1997 and 1999. Culver City was chosen due to its relative diversity. It is one of the few local communities to have a population of 10% or more in each of the four major racial/ethnic groups: nonHispanic Whites (58%), African Americans (10%), Asian Americans (12%), and Hispanics (20%) (U.S. Bureau of the Census, 1994). Culver City is also geographically segregated. This enabled the use of a two-stage probability sample that incorporated block stratification by the four racial/ethnic categories. The sampling frame was obtained from 1990 Census block data. Residential blocks with 20 dwelling units or more (328 total) were assigned to one of nine strata based on their racial/ethnic composition. Fifty two blocks then were selected from each stratum via systematic sampling. Twenty dwelling units per block were selected randomly for survey receipt. A total of 1,040 questionnaires were mailed to city households. …
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".