Reliability of the Core Items in the General Social Survey: Estimates from the Three-Wave Panels, 2006–2014
Bibliographic record
Abstract
We used standard and multilevel models to assess the reliability of core items in the General Social Survey panel studies spanning 2006 to 2014. Most of the 293 core items scored well on the measure of reliability: 62 items (21 percent) had reliability measures greater than 0.85; another 71 (24 percent) had reliability measures between 0.70 and 0.85. Objective items, especially facts about demography and religion, were generally more reliable than subjective items. The economic recession of 2007–2009, the slow recovery afterward, and the election of Barack Obama in 2008 altered the social context in ways that may look like unreliability of items. For example, unemployment status, hours worked, and weeks worked have lower reliability than most work-related items, reflecting the consequences of the recession on the facts of peoples lives. Items regarding racial and gender discrimination and racial stereotypes scored as particularly unreliable, accounting for most of the 15 items with reliability coefficients less than 0.40. Our results allow scholars to more easily take measurement reliability into consideration in their own research, while also highlighting the limitations of these approaches.
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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 | 0.029 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".