Spirituality and Religion: How Does the U.S. Compare With Other Countries?
Bibliographic record
Abstract
Pew Research Center conducted this survey to examine how the United States compares to other parts of the world on a variety of religious and spiritual measures. The survey included some questions grounded in the Christian, Jewish and Muslim traditions, as well as some questions with roots in Buddhism, Hinduism and other Asian faiths. Among the key findings is that in the U.S., seven-in-ten adults think there is definitely or probably an afterlife, which puts the U.S. in the top third of countries surveyed on this question. This analysis is based on surveys conducted in 36 countries on six continents. The countries have a wide array of religious traditions. Some have Christian, Muslim or Jewish majorities, while others have Hindu or Buddhist majorities. A few are quite religiously mixed, and some have large shares of people who are religiously unaffiliated. This analysis allows users to interact with data from these surveys. Users can sort a table by several different columns to see how different countries compare on different religious and spiritual measures. Outside the United States, this analysis draws on nationally representative surveys of 41,503 adults conducted from Jan. 5 to May 22, 2024. All surveys were conducted over the phone with adults in Canada, France, Germany, Greece, Italy, Japan, Malaysia, the Netherlands, Singapore, South Korea, Spain, Sweden and the United Kingdom. Surveys were conducted face-to-face in Argentina, Bangladesh, Brazil, Chile, Colombia, Ghana, Hungary, India, Indonesia, Israel, Kenya, Mexico, Nigeria, Peru, the Philippines, Poland, South Africa, Sri Lanka, Thailand, Tunisia and Turkey. In Australia, we used a mixed-mode, probability-based online panel. For the U.S., data comes from respondents contacted in three separate survey waves in 2023 or 2024: 1. 11,201 respondents were surveyed from July 31 to Aug. 6, 2023, via Pew Research Center’s American Trends Panel (ATP), an online survey panel recruited through national random sampling of residential addresses, which gives nearly all U.S. adults a chance of selection. Read more about the ATP’s methodology. 2. 12,693 respondents were surveyed from Feb. 13 to 25, 2024. Most of the respondents (10,642) in this survey are members of the ATP, and nearly all these panelists also participated in the ATP survey that concluded in Aug. 2023. The remaining U.S. respondents (2,051) in this wave are members of three other panels: the Ipsos KnowledgePanel, the NORC Amerispeak Panel and the SSRS Opinion Panel. All three are national survey panels recruited through random sampling (not “opt-in” polls). We used these additional panels to ensure that the survey would have enough Jewish and Muslim respondents to be able to report on their views. 3. In addition, U.S. data for a few questions comes from 36,908 respondents surveyed from July 17, 2023, to March 4, 2024, as part of the Center’s latest Religious Landscape Study (RLS). This survey was conducted mainly online and on paper, while 3% opted to complete the interview on the telephone. The RLS was made possible by The Pew Charitable Trusts, which received support from the Lilly Endowment Inc., Templeton Religion Trust, The Arthur Vining Davis Foundations and the M.J. Murdock Charitable Trust. This analysis was produced by Pew Research Center as part of the Pew-Templeton Global Religious Futures project, which analyzes religious change and its impact on societies around the world. Funding for the Global Religious Futures project comes from The Pew Charitable Trusts and the John Templeton Foundation (grant 63095). This publication does not necessarily reflect the views of the John Templeton Foundation.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".