cross-national-design

Name: cross-national-design
Author: scdenney

34stars0forks

How to install cross-national-design?

scdenney/open-science-skills/cross-national-design

$npx -y skills add scdenney/open-science-skills --skill cross-national-design

Installs into the current project.

Summary

Design cross-national survey experiments covering power, equivalence, and localization. Use for multi-country sampling, measurement comparability, and instrument adaptation.

Files · 1

View on GitHub

SKILL.md

1	# Cross-National Comparative Designer
2
3	Related skills. This skill composes with `hypothesis-building` (per-country predictions and estimands), `survey-design` (question wording, acquiescence, sensitivity), `conjoint-design` (origin-country stimuli, power), `methods-reporting` (per-country CONSORT, APSA/JARS/DA-RT), and `pre-registration-writing` (study-level PAP with per-country tiers).
4
5	Reference files. `reference/example-4-country-immigration.md` -- worked four-country immigration-conjoint cascade covering case-selection logic, shared attributes with origin-country calibration, the full TRAPD translation protocol, per-country SESOI/predictions, and a pooled-vs-per-country analysis table.
6
7	## Instructions
8
9	### 1. Case Selection and Theoretical Justification
10	- Per-Country Predictions Before Case Selection (Why -> If-Then): Before finalizing the country set, articulate, for each candidate case, the specific pattern of results that would support the theoretical claim versus disconfirm it. Cross-national leverage comes from the contrast between predicted country-level patterns, not from running the same experiment in multiple places and describing what happens. If a case cannot be tied to a distinct, falsifiable prediction, it is decorative rather than diagnostic. See `hypothesis-building` for the Why -> If-Then funnel and estimand specification.
11	- Variation by Design: Cases should be selected to vary on theoretically relevant dimensions (e.g., regime type, institutional structure, immigration history, partisan polarization), not for convenience or data availability. Each case should serve a specific theoretical function identified in the step above.
12	- Case Selection Table: Produce a summary table listing each country, its relevant contextual features (e.g., immigration salience, institutional architecture, regime type), the per-country prediction, and the specific motivation for its inclusion. This table belongs in the PAP and should be referenced in the narrative.
13	- Avoid the "Most Similar" Trap: Cross-national designs are often most informative when cases are deliberately diverse. Including cases that vary on regime type (e.g., democracy vs. hybrid regime) or institutional structure (e.g., parliamentary vs. presidential) enables stronger tests of whether a theoretical mechanism generalizes beyond a single political context.
14	- Typical Case Count (3--5): For survey experiments with ~2,500 respondents per country, 3--5 cases is a common range in published work that balances theoretical leverage with practical feasibility (budget, translation, vendor logistics). Fewer than 3 limits comparison; more than 5 strains resources without proportional analytical gain. Treat this as a planning heuristic rather than a rule and tie the final count to the per-country predictions above.
15	- Information Environment Variation: The information environment differs across countries -- media systems, political knowledge levels, and the accessibility of policy information vary. A treatment that is "informative" in one context may be redundant or incomprehensible in another. Document the expected information environment per country and consider how it affects treatment interpretation (Druckman 2022).
16
17	### 2. Instrument Localization
18	- Conceptual Equivalence over Literal Translation: The goal is not identical wording across countries but equivalent conceptual meaning. A "skilled worker visa" means H-1B in the US, E-7 in South Korea, S Pass in Singapore. Use country-specific referents that carry the same conceptual weight. Word choice constitutes a framing treatment and must be calibrated per country, not just translated -- terms like "unauthorized," "undocumented," and "illegal" carry different connotations across linguistic and political contexts (Stantcheva 2023, citing Merolla et al. 2013). The Cross-Cultural Survey Guidelines (CCSG 2016) are the canonical source for cross-cultural comparability, including translation and adaptation procedures.
19	- Qualitative Treatment Framing: For information experiments fielded across countries, consider using qualitative descriptions rather than exact statistics. Qualitative information "can help make the treatment more homogeneous when doing an experiment in several countries or settings" because exact numbers carry different meanings in different contexts (Stantcheva 2023).
20	- Anti-Acquiescence Measurement: Acquiescence bias varies by culture. Use item-specific scales (not agree-disagree or true-false formats), balanced scales with equal numbers of positive and negative options, and randomized question direction to ensure measurement equivalence across countries (Stantcheva 2023).
21	- **Coarse Measurement as Principled Commitment

People who liked this also viewed

6 picks

Type

cross-national-design

34stars0forks

View on GitHub

How to install cross-national-design?

scdenney/open-science-skills/cross-national-design

$npx -y skills add scdenney/open-science-skills --skill cross-national-design

Installs into the current project.

Summary

Design cross-national survey experiments covering power, equivalence, and localization. Use for multi-country sampling, measurement comparability, and instrument adaptation.

Files · 1

View on GitHub

SKILL.md

1	# Cross-National Comparative Designer
2
3	Related skills. This skill composes with `hypothesis-building` (per-country predictions and estimands), `survey-design` (question wording, acquiescence, sensitivity), `conjoint-design` (origin-country stimuli, power), `methods-reporting` (per-country CONSORT, APSA/JARS/DA-RT), and `pre-registration-writing` (study-level PAP with per-country tiers).
4
5	Reference files. `reference/example-4-country-immigration.md` -- worked four-country immigration-conjoint cascade covering case-selection logic, shared attributes with origin-country calibration, the full TRAPD translation protocol, per-country SESOI/predictions, and a pooled-vs-per-country analysis table.
6
7	## Instructions
8
9	### 1. Case Selection and Theoretical Justification
10	- Per-Country Predictions Before Case Selection (Why -> If-Then): Before finalizing the country set, articulate, for each candidate case, the specific pattern of results that would support the theoretical claim versus disconfirm it. Cross-national leverage comes from the contrast between predicted country-level patterns, not from running the same experiment in multiple places and describing what happens. If a case cannot be tied to a distinct, falsifiable prediction, it is decorative rather than diagnostic. See `hypothesis-building` for the Why -> If-Then funnel and estimand specification.
11	- Variation by Design: Cases should be selected to vary on theoretically relevant dimensions (e.g., regime type, institutional structure, immigration history, partisan polarization), not for convenience or data availability. Each case should serve a specific theoretical function identified in the step above.
12	- Case Selection Table: Produce a summary table listing each country, its relevant contextual features (e.g., immigration salience, institutional architecture, regime type), the per-country prediction, and the specific motivation for its inclusion. This table belongs in the PAP and should be referenced in the narrative.
13	- Avoid the "Most Similar" Trap: Cross-national designs are often most informative when cases are deliberately diverse. Including cases that vary on regime type (e.g., democracy vs. hybrid regime) or institutional structure (e.g., parliamentary vs. presidential) enables stronger tests of whether a theoretical mechanism generalizes beyond a single political context.
14	- Typical Case Count (3--5): For survey experiments with ~2,500 respondents per country, 3--5 cases is a common range in published work that balances theoretical leverage with practical feasibility (budget, translation, vendor logistics). Fewer than 3 limits comparison; more than 5 strains resources without proportional analytical gain. Treat this as a planning heuristic rather than a rule and tie the final count to the per-country predictions above.
15	- Information Environment Variation: The information environment differs across countries -- media systems, political knowledge levels, and the accessibility of policy information vary. A treatment that is "informative" in one context may be redundant or incomprehensible in another. Document the expected information environment per country and consider how it affects treatment interpretation (Druckman 2022).
16
17	### 2. Instrument Localization
18	- Conceptual Equivalence over Literal Translation: The goal is not identical wording across countries but equivalent conceptual meaning. A "skilled worker visa" means H-1B in the US, E-7 in South Korea, S Pass in Singapore. Use country-specific referents that carry the same conceptual weight. Word choice constitutes a framing treatment and must be calibrated per country, not just translated -- terms like "unauthorized," "undocumented," and "illegal" carry different connotations across linguistic and political contexts (Stantcheva 2023, citing Merolla et al. 2013). The Cross-Cultural Survey Guidelines (CCSG 2016) are the canonical source for cross-cultural comparability, including translation and adaptation procedures.
19	- Qualitative Treatment Framing: For information experiments fielded across countries, consider using qualitative descriptions rather than exact statistics. Qualitative information "can help make the treatment more homogeneous when doing an experiment in several countries or settings" because exact numbers carry different meanings in different contexts (Stantcheva 2023).
20	- Anti-Acquiescence Measurement: Acquiescence bias varies by culture. Use item-specific scales (not agree-disagree or true-false formats), balanced scales with equal numbers of positive and negative options, and randomized question direction to ensure measurement equivalence across countries (Stantcheva 2023).
21	- **Coarse Measurement as Principled Commitment

People who liked this also viewed

6 picks

Type