Friendship Network Characteristics and Subjective Well-being
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article explores how friendship network characteristics influence subjective wellbeing (SWB). Using data from the 2003 General Social Survey of Canada, this article differentiates between three components of the friendship network; the number of friends, the frequency of interaction with them and the heterogeneity of the friendship network. The main proposition is that friends bring certain benefits which in their turn increase the level of SWB, rather than that friends directly influence the level of SWB. Benefits considered here are more social trust, less stress, a better health, and more social resources. Results confirm that the influence of the friendship network characteristics mainly works through these benefits. Only the frequency of meeting your friends faceto-face has a relevant remaining direct influence on SWB. Also, differences are found within the relation between friends and the different indicators of SWB. This study, therefore, underlines the importance of looking at the indicators of SWB separately as well as at different characteristics of the friendship network.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it