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Sample & Demographics

Last updated: Apr 13, 2026, 1:39 PM EDT

Demographics are computed independently for each of the four primary result groups. This allows researchers to verify that the composition of their chosen dataset matches their generalizability requirements. All statistics on this page are generated by the daily analysis pipeline.

Demographic Data Sources

Participant demographics are collected from two independent sources. These capture different types of information and should not be conflated:

Survey Demographics (Qualtrics)

Self-reported by participants within the TABS survey instrument itself (questions Q1–Q9). These are role-specific, organizational demographics directly relevant to the research questions.

  • Executive Role (Q1) — CIO, CTO, CEO, CFO, etc.
  • Decision Authority (Q2)
  • Industry (Q3)
  • Organization Size (Q4) — <100 to 10,000+
  • Profit Model (Q5) — For-Profit, Non-Profit, Government
  • Revenue/Budget (Q6–Q7)
  • Geographic Scope & Scale (Q8–Q9)

Source: Qualtrics CSV export → tabs_v2_analysis.py

Platform Demographics (Prolific)

Collected from Prolific’s participant profile database at submission completion. Includes base demographic fields (always exported) and prescreener fields(up to 15 selectable per export from Prolific’s full filter catalog).

Base Fields (always included)

  • Age
  • Sex (as recorded on legal documents)
  • Ethnicity (simplified)
  • First Language
  • Country of Residence & Nationality
  • Country of Birth
  • Student Status
  • Employment Status

Prescreener Fields (configurable, up to 15 per export)

  • Employment Sector (Private, Public, Non-profit)
  • Industry classification
  • Company/Organization Size
  • Occupation/Job Title category
  • Education Level
  • Household Income
  • Fluent Languages
  • Marital Status & Number of Children
  • Health Conditions & Disabilities
  • …and hundreds more via GET /api/v1/filters/

Source: Prolific API POST /studies/{id}/demographic-export/ — snapshot at time of participation

Important: The demographics shown below in the per-group breakdowns are Survey Demographics (Qualtrics)— the organizational and role-based characteristics that participants self-reported in the TABS instrument. Prolific Platform Demographics are available separately via the Prolific demographic export and are not displayed on this page to protect participant privacy.

Cross-Validation: Prolific × Qualtrics Demographic Overlap

Several Prolific prescreener fields overlap with Qualtrics survey demographics, enabling independent cross-validation of self-reported data. Researchers can compare responses to flag discrepancies (e.g., a participant reporting “CIO at a 10,000+ company” in Qualtrics but “Student” or “Company Size: 1–10” in Prolific).

DimensionProlific Field (Platform)Qualtrics Field (Survey)
IndustryindustryQ3_Industry
Organization Sizecompany_sizeQ4_OrgSize
Sectoremployment_sectorQ5_ProfitModel
RoleoccupationQ1_Role

Join key: Prolific Participant ID (PID). Prescreener fields are available when configured as study filters in the Prolific study setup.

Prolific-Only Fields (augment survey data)

Prolific also provides demographic dimensions not captured by the TABS survey instrument, including: Education Level, Household Income, Fluent Languages, Marital Status, Health Conditions, and more. These can be used to augment aggregate demographic reports and assess sample representativeness beyond what the survey captures.

Prolific Study Prescreening Criteria

The following eligibility screeners are configured on the live Prolific study. All participants must match every criterion below to be eligible for recruitment. These prescreener responses are also exported for demographic enrichment and cross-validation against Qualtrics survey responses.

ScreenerCriterionEligible ValuesQualtrics Cross-Ref
Current Country of Residenceis any ofUnited StatesQ8–Q9 (Geography)
Employment Statusis any ofFull-Time—
Employer Typeis any of
  • Employee of a for-profit company or business
  • Employee of a not-for-profit, tax-exempt, or charitable organization
  • Local government employee
  • State government employee
  • Federal government employee
  • Self-employed (not-incorporated)
  • Self-employed (incorporated)
  • Working without pay in family business or farm
Q5_ProfitModel
Company Sizeis any of50–249, 250–999, 1000+Q4_OrgSize
Job Positionis any of
  • C-Level (e.g. CEO, CFO), Owner, Partner, President
  • Vice President (EVP, SVP, AVP, VP)
  • Director (Group Director, Sr. Director, Director)
  • Manager (Group Manager, Sr. Manager, Manager, Program Manager)
Q1_Role

Enrichment Export:All 5 screener filter_ids are included in the Prolific demographic export alongside 2 additional augmentation filters (education level, household income), totaling 7 of the 15-filter API maximum. Screener responses enable cross-validation against Qualtrics survey answers (e.g., Prolific “Company Size: 1000+” vs Qualtrics Q4 “10,000+”). Raw prescreener data is processed ephemerally and never committed to the repository.

Sample Size Summary

#Result GroupDescriptionN
1Conservative CleanProlific APPROVED + all quality checks (IRI, duration >= 540s, reCAPTCHA, straightlining, auth)87
2Flexible CleanProlific APPROVED + basic quality (all 3 IRIs + duration >= 480s)134
3Prolific AcceptedAll deduplicated V2 rows with Prolific APPROVED status243
4All V2 FinishedFinished + duration >= 120s (extreme speeders excluded)391

Survey Demographics by Result Group (Qualtrics)

Each result group below shows its organizational and role-based composition as self-reported by participants in the TABS survey (questions Q1–Q9). This allows assessment of whether data cleaning differentially affects sample composition across executive roles, organization sizes, and sector types.

Conservative Clean (N=87)

Roles

Other1719.5%
CIO1213.8%
COO1112.6%
CEO1011.5%
CMO910.3%
CSO89.2%
CHRO78.0%
CFO66.9%
CTO44.6%
CRO33.4%

Organization Size

<1001112.6%
100-4993034.5%
500-99989.2%
1000-49992124.1%
5000-999966.9%
10000+1112.6%

Profit Model

For-Profit6271.3%
Non-Profit1517.2%
Government/Public Sector1011.5%

Technical vs. Non-Technical Breakdown

Technical (CIO, CTO)1921.8%
Non-Technical (CEO, CFO, COO, CHRO, CMO, CSO, CRO)6878.2%
Other (self-reported)00.0%

Grouping used for ANOVA and effect-size comparisons on the Findings page.

Flexible Clean (N=134)

Roles

CIO2317.2%
Other2317.2%
COO1712.7%
CEO139.7%
CMO129.0%
CFO118.2%
CHRO107.5%
CSO107.5%
CRO86.0%
CTO75.2%

Organization Size

<1001914.2%
100-4994130.6%
500-9991712.7%
1000-49993324.6%
5000-999986.0%
10000+1611.9%

Profit Model

For-Profit9268.7%
Non-Profit2720.1%
Government/Public Sector1511.2%

Technical vs. Non-Technical Breakdown

Technical (CIO, CTO)3324.6%
Non-Technical (CEO, CFO, COO, CHRO, CMO, CSO, CRO)10175.4%
Other (self-reported)00.0%

Grouping used for ANOVA and effect-size comparisons on the Findings page.

Prolific Accepted (N=243)

Roles

Other5020.6%
CIO3815.6%
COO2510.3%
CSO229.1%
CEO218.6%
CMO197.8%
CFO197.8%
CHRO177.0%
CTO156.2%
CRO156.2%
CISO20.8%

Organization Size

<1004418.1%
100-4996125.1%
500-9993414.0%
1000-49995121.0%
5000-9999208.2%
10000+3313.6%

Profit Model

For-Profit18074.1%
Non-Profit4317.7%
Government/Public Sector208.2%

Technical vs. Non-Technical Breakdown

Technical (CIO, CTO)5924.3%
Non-Technical (CEO, CFO, COO, CHRO, CMO, CSO, CRO)18475.7%
Other (self-reported)00.0%

Grouping used for ANOVA and effect-size comparisons on the Findings page.

All V2 Finished (N=391)

Roles

Other7519.2%
CIO5814.8%
CEO4010.2%
COO389.7%
CTO369.2%
CFO338.4%
CSO328.2%
CMO276.9%
CHRO246.1%
CRO235.9%
CISO51.3%

Organization Size

<1005714.6%
100-49911028.1%
500-9995814.8%
1000-49997920.2%
5000-9999328.2%
10000+5514.1%

Profit Model

For-Profit29575.4%
Non-Profit6516.6%
Government/Public Sector317.9%

Technical vs. Non-Technical Breakdown

Technical (CIO, CTO)10426.6%
Non-Technical (CEO, CFO, COO, CHRO, CMO, CSO, CRO)28773.4%
Other (self-reported)00.0%

Grouping used for ANOVA and effect-size comparisons on the Findings page.

Understanding “Other” Roles

Participants who selected “Other (please specify)” for their executive role (Q1) provided a free-text description. The analysis pipeline categorizes these responses into broad groups using keyword matching to provide insight into the composition of the “Other” category without exposing individual responses.

CategoryDescriptionExample Patterns
C-Suite AdjacentChief-level titles not in the standard 9 C-suite optionsCDO, CPO, CAO, CLO, CAIO, Chief Data Officer, Chief Privacy Officer
VP / SVPVice President, Senior VP, or Executive VP titlesVice President, VP, SVP, EVP, AVP
DirectorDirector-level titles across functionsDirector of ..., Senior Director, Group Director
Manager / Program LeadManagement and team-lead rolesManager, Program Lead, Team Lead, Supervisor
Owner / Founder / PresidentBusiness ownership or presidency rolesOwner, Founder, President, Partner, Principal
Technical SpecialistIndividual contributor or specialist technical rolesEngineer, Architect, Analyst, IT Administrator, Security
UncategorizedResponses that did not match any keyword pattern—

Note:These categories are computed automatically by the daily analysis pipeline using keyword matching on free-text responses. A single response is assigned to the first matching category. “C-Suite Adjacent” and “VP / SVP” respondents may represent roles functionally equivalent to the named C-suite titles but with different organizational naming conventions. Researchers may wish to consider reclassifying these into the Technical or Non-Technical grouping for sensitivity analyses.

Privacy Note:Survey demographics (shown above) are aggregated from self-reported Qualtrics responses (Q1–Q9) and displayed as category-level counts and percentages only. Prolific platform demographics (base fields: age, sex, ethnicity, etc.; prescreener fields: industry, company size, occupation, etc.) are collected separately and are used for cross-validation and sample balancing but are not displayed on this page to protect participant privacy. No individual-level data is displayed from either source.

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