An Invitation to
Researchers
Anonymized Program Participation Dataset — Version 6.0
An open dataset on purpose formation — organized around authentic engagement, built across 42 countries, and left for you to analyze.
University Professor or Administrator? View the executive summary with IRB guidance, governance documents, and the class-level request form.
How to Use This Document
The workbook has 19 sheets. This page describes each instrument using three sub-headers:
Instruments are organized into four groups by the type of data they capture. Not every participant completes every step — the pattern of who completes what, and in what sequence, is itself a research question.
What This Dataset Is
In November 2024, Arthur L. Fuller Jr. — a behavioral health executive and doctoral candidate in Indianapolis — launched a free, fully remote, globally accessible program called Voice Up™ Publishing. Its organizing premise: most institutions teach people what to do, but few help them identify what they genuinely care about and connect that to meaningful work.
Fuller calls the gap between those two things the Naming Gap — the subject of his doctoral research at the University of Indianapolis (IRB Study #02135). Voice Up™ is a real-world attempt to close it at scale.
Between November 2024 and June 2026, the program engaged 2,115+ participants across 42 countries and 347 institutions. No one was paid. No one was required to follow a prescribed path. Everyone chose their own cause, pace, and depth. The program provided structure and five shared principles — Collaboration, Humility, Precision, Patience, Empathy — but not prescribed outcomes.
Everything participants said, planned, measured, reflected on, and produced was recorded. That body of records — stripped of all personally identifying information — is what this dataset contains.
Limitations at a Glance
— stated plainly before you beginAssociation is not causation
Every finding here is observational. Name your mechanism explicitly or do not claim it.
Openness does not equal generalizability
A global voluntary program is not a representative sample of any defined population. Be specific about what your findings extend to.
88% DS6 non-completion is not dropout
Framing it that way applies a closed-system model to an open-system design. Use the correct language.
ROC-AUC of 0.98 is in-sample only
It does not mean the model generalizes. Treat it as a hypothesis to validate, not a result to report.
You may find something nobody anticipated
Follow it. Open processes produce surprises. That is not a problem — it is the point.
19 Sheets · 9 Instruments
Each instrument is described with what it is, why it matters, and what to ask.
Mentor Connection Intake
What it is
Four open-ended questions asked at program entry — purpose summary, which principle matters most and why, what help is needed, and a magic wand aspiration. All verbatim. Wave 1 base (145 records) and Wave 2 update (146 records) on separate sheets for direct comparison.
Why it matters
This is the earliest documented moment of purpose articulation in the corpus. The language is unguided and unsolicited.
Example question (many more are possible)
Do principle choices at intake predict what participants do later? How does purpose language vary across 42 countries?
Talent Inventory
What it is
Skill catalog (writing, arts, leadership, finance, governance, languages, and more), self-selected engagement level (1–2 to 15–20 hrs/week), bio, and career goals. Version 9 adds self-reported gender and ethnicity fields.
Why it matters
Documents participant self-assessment of capacity alongside purpose. Enables talent-purpose alignment analysis.
Example question (many more are possible)
Does stated engagement level at intake predict actual hours logged in DS7? Is there a relationship between skill profile and cause chosen in DS10?
Purpose Reflections
What it is
Brief purpose statements and principle alignment responses. Largest single instrument by record count. Wide net — includes participants who went no further alongside those who eventually logged hundreds of hours.
Why it matters
Best instrument for studying the vocabulary of purpose at scale.
Example question (many more are possible)
What words, themes, and domains appear when 849 people describe what they care about? What is absent?
Student Wellbeing Assessment
What it is
Likert instrument (1 = Never, 5 = Consistently) across five domains: Academics, Finances, Social Connections, Precision, Physical Wellbeing. Wave 1 base (DS3) uses 22 items; Wave 2 update (DS3-v23) uses 25 items (adds 3 Physical Wellbeing items). Domain averages pre-computed. Student version alpha = 0.93.
Why it matters
Most statistically powerful instrument in the corpus. Over 1,000 combined records enables subgroup analyses.
Example question (many more are possible)
Do the five a priori domains replicate under factor analysis? Do regional subgroups show different wellbeing profiles?
Wellbeing Self-Assessment v2
What it is
10-item Likert instrument. Two domains: Healthy Balance (workload, balance, rest, stress, eating) and Your Future (career goals, networking, resources, relationships, optimism). Domain averages pre-computed.
Why it matters
Designed for faster administration at a later program stage than DS3. Captures a different slice of the wellbeing picture.
Example question (many more are possible)
How do DS3 and DS9 scores relate for participants who completed both? Some participants completed both instruments during the same time period. If you compare them, specify how you handle temporal overlap — averaging, using the more recent score, or treating them as parallel reliability measures are all defensible approaches.
Fire Planning Document
What it is
Structured purpose plan — cause, personal origin story, target population, success definition, research plan, stakeholders, lesson-tracking method, feedback approach, risk assessment. Eight to twelve substantive verbatim fields per record.
Why it matters
The only instrument that captures how a person translates purpose intention into a structured plan. This is the planning layer that links naming (DS1, DS5) to doing (DS7).
Example question (many more are possible)
Does what people plan here match what they actually do in DS7? How specific are the success definitions?
Intern Hours Log
What it is
Weekly work logs with daily breakdowns — hours per day (Sun–Sat), which principles were applied each day, a written work summary per day, weekly lesson learned, and output URLs for finished deliverables. Spans January 2025 – June 2026. Institutions include Berkeley City College, University of Texas at Austin, Bryant & Stratton College, Marshall University, and 70 others.
Why it matters
Most granular behavioral data in the corpus. Documents purposeful action at day-level resolution.
Example question (many more are possible)
Does principle application shift as an internship deepens? What is the relationship between hours logged and the richness of reflection?
Incubator Application Pipeline
What it is
Seven-step structured application with a $1.49 processing fee. Documents which steps were completed, payment status, and open-text applicant feedback. 88% non-completion rate.
Why it matters
In an open system where participation is never required, 88% non-completion is a self-selection rate, not a dropout rate. This distinction matters for interpretation.
Example question (many more are possible)
What distinguishes the 12% who finished all seven steps? Does DS6 completion predict anything about later DS7 engagement?
Titan of Life Leadership Reflections
What it is
All 408 participants responded to the same ten-minute biographical excerpt about Melvin L. Burks, behavioral health leader. Two questions: Does this story inform your leadership journey? Why is now the right time for you to join Voice Up? All 408 entries have non-blank responses to both questions. Average lengths: 373 characters (leadership reflection), 414 characters (why now). 66.4% said yes to hearing more.
Why it matters
The only instrument where every participant responded to identical stimulus. Enables genuine cross-cultural comparison.
Example question (many more are possible)
When people from 42 countries respond to the same biographical narrative, what is universal and what varies by cultural context?
The Three Analytical Overlays
These are pre-built analyses included as starting points. Treat them as hypotheses to audit, not conclusions to accept.
The Journey Architecture
These instruments grew organically — they were not designed as a battery. Laid out in participant journey order, a coherent progression emerges. The third column is not a description. It is a question.
Not every participant completes every step. The pattern of who completes what — and in what sequence — is itself a research question.
Naming
DS1, DS2, DS5 — What do participants say about who they are and what they care about?
Planning
DS10, DS6 — How do participants translate purpose into structured intention and commitment?
Doing
DS7, DS3, DS9, DS8 — What do participants actually do, and how does wellbeing and reflection evolve?
Before You Claim Anything
This dataset is genuinely interesting. That is exactly when over-claiming is most likely. Five cautions — expanded from the limitations table into interpretive guidance:
Association is not causation.
Every finding here is observational. Name your mechanism explicitly or do not claim it.
Openness does not equal generalizability.
A global voluntary program is not a representative sample of any defined population. Be specific about what your findings extend to and what they do not.
The 88% DS6 non-completion is not dropout.
Framing it that way applies a closed-system model to an open-system design. Use the correct language.
ROC-AUC of 0.98 is in-sample only.
It does not mean the model generalizes. Treat it as a hypothesis to validate, not a result to report.
You may find something nobody anticipated.
Follow it. Open processes produce surprises. That is not a problem — it is the point.
These Are Doors, Not Assignments
The questions below are illustrative examples only — starting points meant to show what is possible, not an exhaustive list.
Many, many more questions can — and should — be asked beyond these. The dataset is open-ended by design. Bring your own questions.
Quantitative
- —
Descriptive analysis of DS3 or DS9 by domain and world region
- —
Exploratory factor analysis of DS3's 22 items — do the five a priori domains replicate?
- —
Audit and attempt to validate the DS-PM predictive model on a holdout sample
- —
Dosage-response analysis: is there a threshold of stage completion above which outcome probability increases non-linearly?
- —
Cross-instrument: for Crosswalk participants in both DS3/DS9 and DS7, does wellbeing score moderate the relationship between hours logged and reflection richness?
Qualitative
- —
Read 20 DS10 records without coding — let the data name itself before imposing categories
- —
Thematic analysis of DS8 across three or more world regions responding to the same prompt
- —
Code DS10 personal origin stories for the type of lived experience animating each cause
- —
Trace one verified producer's arc across all instruments they appear in via the Crosswalk
Mixed Methods
- —
Use DS3 scores to stratify participants, then read DS7 reflections within each stratum
- —
Construct a joint display table: map DS10 planning codes alongside DS7 hours and principle data
- —
Build longitudinal case narratives for participants in four or more instruments
Glossary of Acronyms
All abbreviations and shorthand used in this document, defined in full.
Applied Purpose Science Research Laboratory — the research division of Voice Up™ Publishing Inc.
Area Under the Curve — a measure of how well a predictive model distinguishes between outcomes (used in ROC analysis)
Dataset 1, Version 17 — the Mentor Connection Intake instrument
Dataset 2, Version 9 — the Talent Inventory instrument
Dataset 3, Version 23 — the Student Wellbeing Assessment instrument
Dataset 5 — the Purpose Reflections instrument
Dataset 6 — the Incubator Application Pipeline instrument
Dataset 7, Version 11 — the Intern Hours Log instrument
Dataset 8 — the Titan of Life Leadership Reflections instrument
Dataset 9 — the Wellbeing Self-Assessment (Version 2) instrument
Dataset 10 — the Fire Planning Document instrument
Dataset Predictive Model — a model built on this dataset to predict participant outcomes; ROC-AUC = 0.98 in-sample
Employer Identification Number — a federal tax identification number issued by the IRS (Voice Up™ Publishing Inc. EIN: 33-1932484)
Exploratory Factor Analysis — a statistical method used to uncover underlying structure in a dataset
Institutional Review Board — an ethics committee that reviews research involving human subjects to protect participant rights and welfare
Internal Revenue Service — the U.S. federal agency responsible for tax administration
Letter of Intent — a preliminary document indicating interest in a research or partnership engagement
Memorandum of Understanding — a formal agreement between two institutions outlining mutual obligations (used in the university partnership framework)
Personally Identifiable Information — data that can be used to identify a specific individual (e.g., name, email, address); all PII has been removed from this dataset
Receiver Operating Characteristic — a curve used to evaluate the diagnostic ability of a binary classification model
Receiver Operating Characteristic — Area Under the Curve; a value of 0.98 appears in this dataset and refers to in-sample model performance only
Uniform Resource Locator — a web address; used in DS7 to link to participant-produced work outputs
United States Patent and Trademark Office — the federal agency where Voice Up™ is registered as a service mark (Reg. No. 8,148,220)
Version number — appended to dataset IDs (e.g., DS1-v17 = Dataset 1, Version 17) to indicate instrument revisions over time
Ethical Requirements
These are not suggestions.
Obtain independent IRB approval from your home institution before initiating primary research
Do not attempt to re-identify any participant — including through open-text responses
Cite Voice Up™ Publishing Inc. as source organization in any publication or presentation
Store on encrypted, access-controlled systems. Do not upload to public repositories
Share findings with the organization if useful: info@appliedpurpose.life
Request the Data
To receive the anonymized dataset, email Voice Up™ Publishing Inc. with your name, institution, intended use, and IRB status. Faculty, graduate students, and doctoral candidates are welcome to request access.
Request Access by EmailSchedule a Conversation with the Founder
Arthur L. Fuller Jr. is available to speak with faculty, doctoral candidates, and research teams who want to understand the dataset more deeply before committing to a formal access request.
Schedule via EmailVoice Up™ Publishing Inc.
Applied Purpose Science Research Laboratory
8465 Keystone Crossing, Suite 115 · Indianapolis, IN 46240 · EIN: 33-1932484
info@appliedpurpose.lifeDataset Introduction v4.0 · June 2026
Trademark Notice: Voice Up™ is a registered service mark of J Ellington Publishing LLC (Reg. No. 8,148,220), registered with the United States Patent and Trademark Office on February 24, 2026. International Class 41: Publication of on-line books and magazines. First use in commerce: November 3, 2024. All rights reserved. Unauthorized use of the Voice Up™ mark is prohibited.
© 2026 Voice Up™ Publishing Inc. / J Ellington Publishing LLC · Applied Purpose Science Research Laboratory · 8465 Keystone Crossing, Suite 115 · Indianapolis, IN 46240
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Data Access Information