Introduction

Economic mobility (“mobility”) refers to how a person’s economic well-being changes over a lifetime. Economic mobility is dynamic, shaped by and embedded across cross-sector pathways connecting workforce, education, health, housing, infrastructure, and place that enable opportunities for people (Chetty et al., 2014, 2018; Isaacs et al., 2008; Mitnik et al., 2024; National Academies of Sciences, Engineering, and Medicine (NASEM) 2024; Ramos et al., 2025). “Sector” refers to the interconnected policy and service domains through which economic mobility efforts are organized, including education, employment, health, and housing, all of which operate within broader place-based contexts (Bryson et al., 2006; Chetty et al., 2014; Isaacs et al., 2008; Urban Institute, n.d.). This situates economic mobility within an intersectional framework similar to that used in studying social determinants of health (SDOH), which emphasizes how social and structural conditions jointly influence health and opportunity (Hanneke & Brunskill, 2024). The SDOH framework offers a model for operationalizing the intersection of social, economic, environmental, and structural elements that play into economic mobility (Office of Disease Prevention and Health Promotion, n.d.-b).

Many programs and initiatives operationalize economic mobility narrowly, often by income or employment indicators. This overlooks the cross-sector pathways shaping economic mobility that interact across systems embedded in workforce, education, health, housing, infrastructure, and place (Chetty & Hendren, 2018; Meadows, 2008; National Association of County and City Health Officials & Esri, 2022; Reeves et al., 2018; Solari et al., 2022). Ultimately, this has resulted in fragmented assessments that lack methodological consistency, missed opportunities for coordination, and may overlook the lived experiences of communities, those who support program implementation, policymakers, and other individuals involved with or impacted by economic mobility initiatives (Chetty et al., 2014; NASEM, 2024, 2025; Price, 2025; Reeves et al., 2018). Fragmentation across the field limits the extent to which we understand the impact of policy and program investments (NASEM, 2022, 2024, 2025). A more practical, integrated understanding is needed to examine how mobility is achieved across cross-sector pathways, diverse settings, and community priorities (NASEM, 2022, 2025; Urban Institute, n.d.). This paper describes a scoping review protocol designed to synthesize existing evidence on economic mobility and inform a practical framework for understanding what contributes to economic well-being.

Overview of Economic Mobility

Economic mobility is increasingly prioritized by governments and major philanthropic investors (Allen et al., 2024). State and local governments are now accountable for demonstrating mobility outcomes and need evidence-informed tools that can ensure these investments lead to social impact (Bill & Melinda Gates Foundation, 2023; NASEM, 2024; National League of Cities, 2023; Solari et al., 2022). Recent initiatives, such as Gates Foundation’s Economic Mobility and Opportunity strategy and National League of Cities’ Advancing Economic Mobility, underscore mobility as a priority investment. The National League of Cities (2023) has invested in Advancing Economic Mobility grants and technical assistance to municipalities across the United States. The National Association of Counties (2025) has also invested through its Rural Leaders for Economic Mobility program to support small rural counties with technical assistance and subgrants that can facilitate data-driven decision-making across local governments. These investments expand opportunities to build mobility initiatives. Yet, the theoretical framing around economic mobility remains fragmented across sectors. This leads to a slower pace of generating evidence that may explain mobility impacts. Without integrated frameworks and data, policy-relevant questions regarding economic mobility often remain unaddressed. A practical, integrated framework is needed to better understand which social investments improve mobility and for whom, as well as which pathways and conditions play a role in driving opportunities across different settings (NASEM, 2022, 2025).

More broadly, there are existing gaps related to data silos, lack of consistent metrics, and lack of standardized definitions for mobility across the field (Reeves et al., 2018). This limits the ability to drive meaningful comparisons of cross-sector initiatives designed to improve mobility outcomes (Chetty et al., 2014; Saez & Zucman, 2016). The National Academies of Science, Engineering, and Medicine (2022, 2025) have called for an integrated model that can examine economic mobility with an intersectional perspective of multiple sector pathways as well as an explicit need to examine why and how place matters. This call is similar to existing SDOH models that have been operationalized through larger national objectives such as the Healthy People 2030 campaign, to measure the U.S.'s progress in critical areas of public health, including economic stability, education access and quality, health care access and quality, neighborhood and built environment, and social and community context (Office of Disease Prevention and Health Promotion, n.d.-b, n.d.-a). This review draws on that organizing logic while focusing on domains most commonly identified in the economic mobility literature. In particular, we propose recognizing place and place-based strategies or programs as integral to our cross-sector framework for economic mobility. Place-based strategies refer to right-sized, local-driven approaches for community development tailored by unique characteristics of a geographic location (Rodríguez-Pose & Wilkie, 2017). Examples of these include Head Start and Promise Neighborhoods—both of which are place-based and early learning programs—that operate through interconnected pathways that begin early in life and extend across education, health, family stability, and place. These initiatives show why mobility needs an integrated framework capable of capturing multiple sectors of opportunity and longer-term effects on children and families. With narrow mobility measures, interactions among underlying drivers of opportunity and disadvantage are overlooked (Braveman & Gottlieb, 2014; Heckman, 2006; Marmot et al., 2008). This creates a cap on the field’s ability to demonstrate impact and guide transformative policy for communities.

In addition to conceptual and methodological variability, there is limited attention to how economic mobility is defined and measured in partnership with communities, including individuals most directly impacted, organizations, and policymakers (NASEM, 2024, 2025). Much of the existing evidence relies on administrative or observational data, often excluding community perspectives in shaping what outcomes matter and how they should be assessed. However, community perspectives are increasingly recognized as important for identifying locally meaningful priorities, interpreting quantitative indicators, and ensuring that measures reflect lived experience rather than administrative data alone (Centers for Disease Control and Prevention, 2024; Ellsworth et al., 2026; Hacker et al., 2022; Price, 2025). This gap limits the field’s ability to produce measures that reflect community-defined priorities, local realities, and pathways to mobility that extend beyond traditional indicators. This also aligns with broader calls for the field to embed community engagement in designing mobility with the practice-based expertise of communities involved with or impacted by economic mobility (NASEM, 2024, 2025).

This study protocol describes a scoping review (ScR) that will examine the current landscape on economic mobility through a multisector lens, highlighting cross-cutting patterns, strengths, and opportunities to address gaps. ScRs are useful tools to understand the breadth of evidence on a particular topic, identify contextual factors related to a specific recommendation, and identify potential strategies for implementation (Munn et al., 2022; Pollock et al., 2024). ScRs are also considered strategic investments that can consolidate existing evidence to inform more coherent and scalable frameworks (Pawson et al., 2005; Pollock et al., 2024; Segur-Ferrer et al., 2024). While economic mobility appears to be widely studied, existing reviews tend to focus on individual topic areas such as education or health (Reeves et al., 2018). There are limited integrative reviews that examine how each of these sectors collectively shape economic mobility. To the authors’ best knowledge, this is the first structured ScR that comprehensively examines economic mobility sectors with an integrated lens. In combination with engagement of state and local representatives involved in economic mobility, the protocol outlines how the ScR will map and synthesize existing measures for economic mobility with practice-based expertise.

Objective

The planned ScR will examine the current state of the field on economic mobility to synthesize how mobility is defined, measured, and examined. The ScR will focus on conceptualizing economic mobility across five a priori domains: (1) place-based strategies, (2) workforce pathways, (3) housing stability, (4) early childhood supports, and (5) digital access. These areas were selected based on a preliminary review identifying the structural, social, and economic pathways most frequently associated with economic mobility (Chetty et al., 2014; Ochillo, 2022; Rodríguez-Pose & Wilkie, 2017; Solari et al., 2022; Urban Institute, 2022). The selection of key domains will also be used to limit the scope for feasibility to complete within the constraints of the project’s timeline and budget. The following four aims to meet this objective will guide the review:

  1. Identify and describe how economic mobility is defined.

  2. Identify and describe key mobility domains and how these have been examined, in what settings, and with whom, to the extent possible.

  3. Identify the most common domains in state and local materials using gray literature.

  4. Identify patterns and gaps across domains that may inform future development of an economic mobility framework.

Methods and Analysis

This protocol paper is structured using the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) statement to describe how we will conduct the ScR activities (Moher et al., 2015). The ScR will be guided by Arksey and O’Malley’s scoping review methodological framework and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines (Arksey & O’Malley, 2005; Page et al., 2021; Tricco et al., 2018). In addition to the stages described by Arksey and O’Malley, this review incorporates a dedicated reviewer and artificial intelligence (AI) calibration stage prior to formal screening. This stage is intended to ensure consistent application of eligibility criteria, establish reviewer agreement, and provide a sufficiently representative training set for DistillerSR’s natural language processing (NLP)–based prioritization functions (e.g., Continuous AI Reprioritization, AI Audit, and AI Simulation) and selected generative AI-assisted extraction functions (e.g., Smart Evidence Extraction) before implementation in the screening and extraction workflow. DistillerSR is an AI-assisted systematic review platform that helps optimize and accelerate review processes with machine learning tools (Hamel et al., 2020; Silva et al., 2026).

Additional best practices will be implemented to ensure rigor and comprehensiveness, including a team approach, initial consultation with subject matter experts (SMEs), and piloting materials for consistency (Pollock et al., 2023) (Table 1). These practices have promoted successful completion of prior reviews published in high impact journals (Bustos, 2020; Bustos et al., 2025; Hailemariam et al., 2019, 2024; Montrosse-Moorhead et al., 2024). Expert consultations with three or four SMEs will aim to discover how state and local representatives define and measure mobility in their respective settings and what type of data would benefit their work. SMEs include organizational representatives involved in economic mobility initiatives or work across sectors that shape economic mobility.

This study is preregistered on Open Science Framework (OSF) (https://osf.io/f57h4/overview). Modifications to the protocol will be made available on the OSF platform. Of note, no other similar or active reviews were found in OSF or PROSPERO.

Table 1.Practices to enhance rigor
Best practices Description of activities
Reviewer experience and training We will use a standardized protocol with training led by an author team with expertise in systematic review methods and AI.
Continued involvement Screening will be conducted by experienced reviewers who will be involved throughout the project (e.g., defining the review aims, scope, and criteria) for consistency.
Piloting process for reliability and calibration We will pilot the screening process to establish reliability with the review team and calibration with AI tools prior to independent screening using a set of practice articles. This will refine the process for clarity and ensure consistency in review assessments.
Team approach with reviewer and expert consensus If pairs of reviewers cannot come to a clear decision, there will be consensus discussions with the full team. When reviewers cannot confidentially come to a decision, a third reviewer with mobility expertise will be consulted.
Responsible AI-assisted screening DistillerSR's AI-supported features will be used to improve screening and data-charting efficiency while maintaining human oversight. An initial training set will be screened by reviewers to train the model, after which Continuous AI Reprioritization may be used to prioritize likely relevant records for human review. Following screening, AI Audit and random verification of low-priority records will be used as quality assurance procedures to reduce the risk of false exclusions.
During data charting, DistillerSR's Smart Evidence Extraction (SEE) capabilities may be used to identify, extract, and link supporting evidence from included articles. All AI-generated screening recommendations and extracted data elements will be reviewed and verified by human reviewers prior to final inclusion in the dataset.

Adapted from Walsh-Bailey et al. (2023) and Bustos et al. (2025).

Stage 1: Defining the Scoping Review Approach and Research Questions

Research questions were based on gaps identified in prior reviews conducted on “economic mobility,” team discussions, and input from other SMEs involved with economic mobility initiatives or programs in their respective settings. The research questions are designed to advance current knowledge gaps and guide future efforts to develop actionable, and contextually relevant approaches to examine economic mobility (Table 2).

Table 2.Study aims and questions
Aims Research questions
Aim 1: Identify and describe how economic mobility is defined. RQ1: How has economic mobility been defined in the field?
Aim 2: Identify and describe key mobility domains and how these have been examined, in what settings, and with whom, to the extent possible. RQ2A: What key mobility domains have been examined, and how have they been operationalized, in which settings and with which populations?
RQ2B: What are the methodological and contextual characteristics of the studies (e.g., designs, analyses, and outcomes)?
Aim 3: Identify the most common domains in state and local materials using gray literature. RQ3: What domains (i.e., place-based strategies, workforce pathways) are most commonly solicited in state and local materials to promote economic mobility?
Aim 4: Identify patterns and gaps across domains that may inform future development of an economic mobility framework. RQ4: What patterns and gaps emerge from the evidence that may inform an evidence-based mobility framework?

The Sample, Phenomenon of Interest, Design, Evaluation, and Research type (SPIDER) framework was used to guide the development of inclusion and exclusion criteria and inform the search strategy (Cooke et al., 2012). SPIDER is well suited to exploratory research questions, particularly those focused on study design and broader forms of evidence rather than clinical outcomes, making it appropriate for the objectives of this review. DistillerSR will be used to manage data throughout the project. The platform has been used successfully across a multitude of studies ranging from evidence gap analyses on environmental exposures to metals (Hester et al., 2022) to systematic reviews on patient safety events in health care settings (Bowman et al., 2023).

Following findings from research into the efficacy of AI-assisted literature reviews, we will utilize DistillerSR to complement instead of fully replace human reviewers (Yao et al., 2024). The scoping review will be informed by consultation with SMEs with expertise in economic mobility initiatives or who work across sectors that shape economic mobility. SME input will inform search strategies, analysis of findings, and translation of the review findings.

Stage 2: Identifying Relevant Literature

The search process will include a multipart search strategy comprised of a literature review (Strategy 1), a supplemental review using manual and AI-assisted searches of gray literature (Strategy 2), and an additional search of citations in selected records with expert consultations (Strategy 3) (see Table 3 and Appendix I at https://osf.io/yu4rm for full search strategy). While the Strategy 1 search may emphasize peer-reviewed literature; supplemental searches through Strategy 2 and 3 will incorporate additional materials, with attention to source credibility and quality. This search process will provide a balanced approach through identifying a comprehensive set of resources across a dispersed body of work in articles, technical reports, and tools. Our search process is intended to capture research and practice-based resources to understand how economic mobility is currently examined.

The search strategy is limited to five domains: (1) place-based strategies, (2) workforce pathways, (3) housing stability, (4) early childhood supports, and (5) digital access. Using preliminary reviews of literature on economic mobility and early discussions with four SMEs, the aforementioned domains were identified as the most reported (Chetty et al., 2014; Ochillo, 2022; Rodríguez-Pose & Wilkie, 2017; Solari et al., 2022; Urban Institute, 2022).

The search is also bounded by a timeframe of 2019–2026. This timeframe was selected to capture recent developments in economic mobility research, particularly given growing investments in mobility initiatives (Bill & Melinda Gates Foundation, 2023; NASEM, 2024, 2025; National League of Cities, 2023; Solari et al., 2022). This timeframe also supports the ScR’s goal of informing a practical and contemporary framework for use by state, local, and community partners. Limiting the scope was also important for feasibility to complete the project in time and within budget.

Search terms used across all searches will include combinations of keywords related to economic mobility and its pathways, including:

economic mobility, economic mobility pathways, economic pathways, economic well-being, social mobility, socioeconomic mobility, upward mobility, upward mobility pathways, place-based strategies, workforce pathways, housing stability, early childhood supports, technology access, financial mobility, wealth mobility, intragenerational mobility, economic opportunity, geographic mobility, life course mobility, childhood disadvantage, equitable economic development, income mobility, earnings mobility, neighborhood opportunity

Table 3.Description of the multipart search strategy
Multipart search strategy Databases Strategy description
Strategy 1: Literature review PubMed, Web of Science, EconLit, and Overton Policy Limited to peer-reviewed and gray literature published between 2019 and 2026 using RTI International’s Library Services. Gray literature captured in these databases may consist of documents produced by governments, professional organizations, research institutes, or nonprofits that are disseminated outside traditional peer-reviewed channels (e.g., technical reports, policy documents, toolkits).
Strategy 2: Targeted gray literature review Publicly available organizational websites, proposal repositories, technical report libraries, and practical tool repositories relevant to economic mobility.
Examples of these sources include the Upward Mobility Fund Open Call Applicant Package, Results for America’s Economic Mobility Catalog, and Public Agenda’s Toolkit on Pathways to Economic Mobility.
Organizational websites will be selected if organizations have existing formal mobility-focused initiatives or centers, produce methodological and citable outputs, and offer tools, frameworks, or other resources relevant to one or more economic mobility domains.		 Manual and AI-assisted searching will identify additional gray literature that may not be captured in RTI’s library databases.
Additional manual searching will be conducted on websites of leading organizations in the economic mobility field. The organizations searched, URLs, and search dates will be recorded in an audit log and summarized in an appendix.
Strategy 3: Citation chaining with expert consultation Reference list of included records, expert-nominated materials, and publicly available reports, tools, or works in progress recommended by SMEs. This supplemental search will identify additional relevant documents that may have been missed through prior searches, consistent with scoping review guidance for mapping broad evidence bases (Arksey & O’Malley, 2005; Levac et al., 2010).

During full-text review, reviewers may identify additional potentially relevant sources cited in article introductions, background sections, discussions, or reference lists. Using Strategy 3, sources that appear relevant based on their title, citation context, or description will be retrieved when feasible. Reviewers may also examine cited tools, frameworks, reports, programs, or policy documents when they appear directly relevant to the review questions. SMEs in economic mobility will also be asked to identify additional reports, tools, or works in progress that are accessible and relevant to the review. Because Strategy 3 is intended to supplement rather than replace database searching, all expert-nominated and citation-chained sources will be screened using the same eligibility criteria as records identified through Strategy 1 and 2. Any relevant documents identified through the search processes will be retrieved to the extent possible and added to DistillerSR.

Stage 3: Reviewer Training and Calibration

Before formal screening and data charting begin, all reviewers will complete a structured training and calibration process to promote consistent application of the review protocol. Training will include a walkthrough of the review objectives, SPIDER-aligned eligibility criteria, screening decision rules, data-charting variables, and DistillerSR forms and functions. Reviewers will also complete practice exercises using a selected set of records representing clear inclusions, clear exclusions, and potentially ambiguous cases. Because the review incorporates AI-assisted prioritization, this calibration stage serves both reviewer training and AI preparation. Establishing consistent reviewer decision-making before formal screening is intended to provide a reliable training set for DistillerSR’s machine learning functions and reduce the potential for variability in eligibility decisions to influence AI predictions.

Calibration will occur in two phases and is designed to support both reviewer agreement and responsible implementation of AI-assisted screening. First, all reviewers will independently screen an initial set of at least 50 titles and abstracts. Screening decisions will be compared in DistillerSR, and the review team will meet to discuss discrepancies, clarify the interpretation of eligibility criteria, and document consensus-based decision rules. If possible, inter-rater reliability will be assessed using Cohen’s kappa, with a target threshold of κ ≥ 0.75, where if agreement falls below the target, reviewers will complete additional calibration exercises before proceeding. If not possible, discussion of disagreements will be held in consensus meetings.

Second, before data charting begins, all reviewers will independently extract data from an initial set of included documents using the structured charting form. Results will be compared to identify differences in variable interpretation, charting practices, and the level of detail recorded. The team will refine variable definitions, response categories, and charting guidance as needed, with all changes documented in the protocol, decision log, and DistillerSR audit trail. Calibration will continue throughout the review through periodic duplicate screening and charting, regular reviewer meetings, and targeted discussion of uncertain or discrepant cases. New or revised decision rules will be documented and communicated to all reviewers to ensure consistent implementation across subsequent stages of the review.

Stage 4: Record Selection

To improve efficiency while maintaining transparency and auditability, the review will use responsible AI-assisted screening within DistillerSR (DistillerSR Inc., 2021). All potentially relevant records identified through the multipart search process will be imported into DistillerSR, where automated and manual deduplication procedures will be used to identify and remove duplicate records referring to the same report or study.

Title Screening

Title and abstract screening will be conducted using the SPIDER-aligned eligibility criteria presented in Table 4. These criteria will apply across all research questions and will guide inclusion and exclusion decisions. DistillerSR’s Continuous AI Reprioritization feature will be used to iteratively learn from reviewer decisions and reorder unscreened records according to their predicted likelihood of meeting the eligibility criteria. This approach is intended to surface potentially relevant records earlier in the screening process while maintaining reviewer oversight and a transparent audit trail (Gartlehner et al., 2019; Hamel et al., 2020; Silva et al., 2026).

At least 25 percent of all titles and abstracts will be screened independently by two reviewers. Inter-rater agreement will be assessed using Cohen’s kappa statistic, with a target threshold of κ ≥ 0.75 (Cohen, 1960). Disagreements will be resolved through discussion and consensus or, when necessary, consultation with an additional member of the review team. Once agreement has been established, the remaining records may be screened by a single reviewer. During this process, DistillerSR’s Continuous AI Reprioritization function will be used to iteratively reorder unscreened records according to their predicted likelihood of meeting the eligibility criteria. AI-generated predictions will be used to prioritize records for human review and will not independently determine study inclusion or exclusion. All eligibility decisions will remain under human oversight.

As an additional quality assurance measure and after screening is complete, DistillerSR’s AI Audit tool will be used to efficiently identify records that may have been incorrectly excluded. Records flagged as potentially relevant will be reevaluated by the review team. DistillerSR’s AI Simulation tool may be used descriptively to characterize the screening process and document implementation experience.

Full-Text Screening

For records that appear potentially eligible following title and abstract screening, full text and any relevant supplementary materials will be retrieved. Two independent reviewers will assess the full-text materials against the eligibility criteria presented in Table 4. Disagreements will be resolved through consensus or consultation with an additional reviewer. When multiple reports describe the same program, initiative, study, or project, the documents will be linked using authorship, project name, study population, setting, intervention characteristics, or other relevant identifiers. Related documents may be treated as a single asset or evidence cluster when appropriate. The review team may contact study or report authors when clarification or missing information is necessary to determine eligibility. Following full-text assessment and any required clarification, final inclusion and exclusion decisions will be documented in DistillerSR. Eligible records will then advance to data charting.

Table 4.SPIDER-aligned eligibility criteria
SPIDER domain Inclusion criteria Exclusion criteria
Sample Must be focused on U.S. contexts, populations, and settings.
  • Studies conducted primarily in international settings will not be included. Some eligible studies may include synthesis of literature that includes both U.S. and international evidence may be considered when the U.S. findings are sufficiently relevant.
  • The document must address relevant populations.
  • Ineligible populations would include theoretical or simulated populations, non-human populations, populations outside of the United States or other non-comparable contexts.
Phenomenon of Interest Must focus on economic mobility or related domains aligned with the study definition.
  • Economic mobility is defined as how a person’s economic well-being changes over time and is shaped by systems across sectors spanning workforce, education, health, housing, and infrastructure that enable opportunities.
  • Record is not focused on economic mobility or tangentially mentions economic mobility as a discussion point or implication.
Must present at least one domain of economic mobility related to the following:
  • Place-based strategies
  • Workforce pathways
  • Housing stability
  • Early childhood supports
  • Digital access
  • Records will be excluded if they do not substantively involve economic mobility, including its outcomes, domains, pathways to impact, or related mechanisms.
Design Publication is a peer-reviewed article; Technical reports are from reputable institutions.
  • Eligible materials may include peer-reviewed articles and gray literature, including technical reports or other documents from reputable institutions (e.g., government agency, academic center, recognized nonprofit, funder, or peer-reviewed report publisher).
  • Records that are not peer reviewed will be assessed for quality and credibility.
  • The record must not be an editorial, opinion piece, or news/media report.
  • Records will be excluded if sources cannot be assessed for credibility. Non-peer-reviewed status alone will not be an exclusion criterion.
Evaluation Must include a sufficient description of the economic mobility strategy or domain utilized to allow for meaningful, reliable charting.
  • The record does not provide a description of the specific economic mobility domain or strategy.
Research type Must be written in English and published between 2019 and 2026
  • Records published outside the 2019–2026 timeframe, not available in English, unavailable for review, or from sources that cannot be assessed for credibility will be excluded.

Stage 5: Data Charting

Once the final set of included records has been identified, data charting will be conducted in DistillerSR using a structured charting form developed specifically for this review. The form is aligned with the review aims, research questions, and conceptual framework and will support standardized collection of information across all included records while preserving a transparent audit trail.

DistillerSR’s Smart Evidence Extraction (SEE) capabilities may be used to support data charting by identifying, extracting, and linking supporting evidence from included full-text records to predefined charting fields. Automated extraction may be used for selected structured data elements to improve consistency and reduce reviewer burden. Consistent with the review’s human-in-the-loop approach, reviewers will verify AI-generated outputs, modify extracted content as necessary, and remain responsible for all final charting decisions. Table 5 presents the planned data-charting framework.

Table 5.Data-charting framework
Area Data element Operational definition/prompt Response format
Bibliographic information Title Article or report title Free text
Document type Type of source Peer-reviewed article; working paper; technical report; policy brief; other
Source Journal, publisher, institution, or other source Free text
Year published Publication year Numeric/free text
Economic mobility construct Theory or framework Theory or conceptual framework informing economic mobility, if any Free text
Definition Definition of economic mobility or another term used by the authors Free text
Population of focus Broader population level or comparison group intended to be addressed by the study National distribution; cohort-specific; peer group; parents or dyads; other
Geographic scope Geographic area covered by the study Free text
Time period Study or measurement period, if applicable Free text
Measurement data source Data source used to measure economic mobility (i.e., dataset, longitudinal survey, administrative record system) Free text
Construct name Name of the mobility construct used by the authors Free text
Construct operationalization How the mobility construct was defined and operationalized Free text
Construct measure Instrument, survey item, administrative field, or other measure used Free text
Study characteristics Analytic sample Sample examined for the mobility construct Free text
Sector or setting Sector or setting, such as workplace, school, or another context Free text
Study design Design of the study reported in the article Free text
Data collection Whether the study used primary, secondary, or both types of data Primary; secondary; both; other
Data analysis method Method or methods used to analyze the data Free text
Primary research questions Main research question or questions Free text
Research hypothesis Hypothesis or hypotheses, when reported Free text
Findings and appraisal Key findings Summary of the study's principal findings Free text
Limitations Limitations reported by the authors or identified during review Free text
Community engagement Community role in measurement Role of community members in defining, measuring, or interpreting mobility Not involved; interprets findings; shapes indicators; co-defines mobility; other
Engagement approach Level or approach of community engagement None; inform (e.g., interviews/lived experience); consult (feedback/advisory); collaborate (codesign/shared interpretation)

The charting framework will capture bibliographic and document characteristics; definitions and conceptualizations of economic mobility; mobility-related domains, strategies, and measures; populations and geographic settings; study designs and analytic methods; outcomes and key findings; community-engagement dimensions; and reviewer notes. Place-related information, including geographic scope, setting, population, and contextual characteristics, will be captured when reported so that the resulting dataset can support subsequent spatial and place-based analyses. Consistent with the review aims to understand how economic mobility is defined and operationalized, the charting framework will explicitly capture whether and how communities were engaged in defining and measuring mobility.

The review will also track characteristics of the evidence base that are relevant to interpretation and application, including study designs, data sources, analyses conducted and how results were applied in practice. This will allow the review to characterize not only the volume and distribution of available evidence but also its potential relevance for informing economic mobility tools, strategies, policies, and conceptual frameworks.

Data charting will use a primarily deductive approach guided by the predefined review questions while allowing for iterative refinement when relevant concepts emerge from the evidence base (Bernard, 2017; Hsieh & Shannon, 2005). The complete list of variables to be charted will be maintained in the protocol on OSF. Any new or revised variables identified during charting will be documented in the protocol and incorporated into the DistillerSR charting form as appropriate. The community-engagement variables included in the charting form will capture whether and how community members contributed to defining, measuring, interpreting, or applying economic mobility concepts. These data will be used to identify gaps and opportunities for strengthening community participation in future research, measurement, and implementation.

Reviewers will chart information as reported in the source material and will avoid inferring, calculating, or assigning values that are not explicitly supported by the source. When information is absent, unclear, or not applicable, this will be documented using standardized response categories. DistillerSR’s comparison, audit, and export functions will be used to support quality assurance, document coding decisions, and produce the finalized dataset for analysis. Consistent with the purpose of a scoping review, the review will map the range, characteristics, and distribution of available evidence rather than formally assess the methodological quality or risk of bias of individual studies (Montrosse-Moorhead et al., 2024; Tricco et al., 2018).

Stage 6: Collating, Summarizing, and Reporting the Results

Following completion of data charting, the review team will collate, summarize, and report the findings in accordance with the scoping review aims and objectives. DistillerSR will serve as the central platform for organizing extracted data, maintaining an audit trail of screening and charting decisions, and exporting structured datasets for synthesis and reporting. This approach will support a systematic, transparent, and reproducible review process.

Quantitative and qualitative methods will be used to synthesize the results, as appropriate. Descriptive analyses will summarize the frequency and distribution of economic mobility domains, measures, populations, geographic settings, study designs, outcomes, and community-engagement approaches identified across the included evidence. Findings may be stratified by publication type, geographic scale, population group, sector, or other characteristics relevant to the review questions. Thematic analysis will be used to identify and categorize recurring theories, frameworks, concepts, outcomes, implementation considerations, and other patterns related to economic mobility (Braun & Clarke, 2006, 2021). Quantitative and qualitative findings will be integrated to map the breadth and characteristics of the evidence base, identify areas of concentration, and highlight substantive, methodological, geographic, and population-level gaps. Results will be presented through narrative synthesis, summary tables, evidence maps, conceptual diagrams, and other visualizations, as appropriate. Any refinements to analytic categories or groupings that emerge during the synthesis will be documented and reported transparently through the OSF project page. Because the review will capture geographic scope, settings, populations, and other place-related characteristics, the extracted data will also lend themselves to subsequent place-based analyses. These analyses may help identify where mobility-related evidence is concentrated and where sectors remain under-addressed.

The findings will also inform the development of an evidence-informed economic mobility framework following the three-phase approach described by McMeekin et al. (2020). The framework will integrate the scoping-review findings with consultation from state and local organizational representatives to assess the relevance, clarity, and comprehensiveness of the identified domains and framework components. Feedback from these discussions will be incorporated into the review’s final summaries and reporting before publication of results.

Ethics

The study being conducted does not include human participants and, as such, does not require approval from an institutional review board.

Discussion

This study protocol outlines a structured scoping review that will examine the current state of the field on economic mobility with an integrated lens on (1) place-based strategies, (2) workforce pathways, (3) housing stability, (4) early childhood supports, and (5) digital access. This is the first ScR that will synthesize key mobility sectors together, addressing gaps from previous studies that consider these factors separately using PRISMA guidelines (Reeves et al., 2018). With a cross-impact lens, the planned review has anticipated contributions that will advance future studies and offer a comprehensive framework that may broaden understanding of impact from mobility initiatives. This ScR protocol also has several potential contributions and strengths that relate to responsible AI methodologies within scoping review guidelines, advancing conceptual clarity of economic mobility, engaging practice-based expertise into knowledge generation and translating evidence into tools for action.

Responsible AI Methodologies within Scoping Review Guidelines

This protocol incorporates both AI-assisted prioritization during screening and AI-assisted evidence extraction during data charting, with reviewer verification integrated throughout each stage of the review process. It provides an early example of responsible AI-assisted evidence synthesis in the field of economic mobility. Economic mobility research is distributed across multiple disciplines and sectors, which can make comprehensive evidence identification and screening difficult. The use of AI-assisted prioritization within a reviewer-governed workflow may improve the feasibility of synthesizing this broad literature while preserving transparency, human oversight, and verification procedures (Flemyng et al., 2025; Ge et al., 2024).

A potential contribution of this protocol is the formal inclusion of reviewer and AI calibration as a discrete methodological stage preceding record selection. Although AI-assisted screening tools are increasingly available, limited guidance exists regarding how reviewers should prepare training datasets, establish calibration thresholds, document decision rules, and evaluate model performance before implementation and during protocol development (Flemyng et al., 2025; Ge et al., 2024). By explicitly describing these procedures, the protocol extends current ScR practice and provides a transparent framework for integrating AI-assisted screening while maintaining methodological rigor, reproducibility, and human oversight. Reviewer and AI calibration are treated as complementary processes designed to improve consistency in eligibility decisions while ensuring that AI prioritization and extraction are informed by a representative and well-characterized training set.

By documenting the use of AI-assisted screening, audit functions, recall thresholds, and human review, the study may offer a replicable model for researchers examining other complex concepts that span disciplinary and sectoral boundaries. This review may also contribute to the methodological literature on conducting scoping reviews, particularly those that incorporate AI-assisted efficiencies while maintaining established standards for transparency, reproducibility, and reviewer oversight. This contribution responds to growing calls for greater evaluation, validation, and responsible adoption of AI-assisted evidence-synthesis methods (van Mossel et al., 2025). It may also extend lessons from fields such as conservation science, where AI-supported approaches have been used to improve the efficiency of broad and interdisciplinary reviews (Chang et al., 2025). The review will not establish the effectiveness of AI-assisted screening on its own, but it will provide a documented application that can inform future methodological assessment.

Conceptual Clarity on Economic Mobility

A second anticipated contribution is a clearer account of how economic mobility is conceptualized and operationalized across the literature. The review will compare definitions, metrics, analytic approaches, populations, and settings rather than assume a single established meaning of mobility (Meadows, 2008; NASEM, 2024, 2025; Reeves et al., 2018; Solari et al., 2022). This process may reveal areas of convergence, conceptual differences, and areas frequently measured in isolation. The scoping review protocol outlines a model for synthesizing a definition for mobility with an integrated impact lens, incorporating multiple sectors, measures, settings, and populations. This has the potential to offer more conceptual clarity that combines different types of mobility and pathways—directly responding to a national call for more integrated models and measures (NASEM, 2024, 2025). With conceptual clarity, there is strong potential to advance an approach that can measure more comprehensive impacts from mobility initiatives, offering different perspectives of the same story.

Engaging Practice-Based Expertise into Knowledge Generation

In addition to the evidence-based synthesis, the protocol describes how practice-based expertise from state and local organizational representatives involved in economic mobility will inform different phases of the project. These phases include the development of research questions, interpretation of findings, and refinement of the results framework. This engagement will ground the evidence synthesis on real-world practice, strengthening relevance and usability of results across diverse settings. This addresses a significant gap in community-defined priorities, contextual realities, and pathways to mobility that may be overlooked in traditional approaches (NASEM, 2024, 2025). While the project will not consult individuals from general populations most directly impacted by economic mobility, the project’s engagement approach offers a model for state and local organizations to build on with deeper community engagement. Continuing to embed practice-based expertise with local experiences may strengthen cultural alignment, relevance, and buy-in for economic mobility measurement.

Translating Evidence into Action

By synthesizing evidence across domains and identifying common measures and gaps, the planned review may help support more consistent approaches to understanding and assessing economic mobility across settings. For example, the review will extract information on geographic scope, setting, populations, programs, and other local characteristics that may support subsequent spatial analyses in future studies. These data could be used to further examine the geographic distribution of mobility-related supports, barriers, interventions, and evidence. They may also help identify places or populations that are underrepresented in the literature and other areas that have received limited attention within particular regions. Linking evidence synthesis with geospatial analysis could support more locally responsive research and planning, although the review itself will not produce definitive estimates of neighborhood-level mobility or causal spatial relationships. An anticipated use of the planned review findings is informing a cross-sector economic mobility framework that can be used in research, program planning, measurement, and policy analysis and evaluation. The framework will organize findings across domains and continue to incorporate input from state and local organizational representatives to assess their practical relevance.

Limitations and Strengths

This protocol is not without limitations. First, the exclusion criteria limit articles to empirical studies that are available in English and published in the United States. These criteria were selected to ensure consistency in data sources and to focus on economic mobility within the context most relevant to U.S. policy and practice. However, the eligibility criterion may overlook other studies that offer additional insights into economic mobility from a global perspective. The protocol is intended for economic mobility initiatives and programs following a U.S.-based context. Transparency in the usability of the framework will be communicated as well as considerations needed for cultural adaptations across other settings. Additionally, the review is bound to five prioritized domains because they are most reported, leaving out a broader range of factors shaping mobility. However, other relevant domains that appear salient in the synthesis will be reported in the results and framework, allowing for flexibility to address other focus areas if they emerge as prevalent in the review.

Despite these limitations, the protocol presents several strengths and potential contributions that may advance knowledge on recent developments made in economic mobility. Strengths to the protocol include the use of evidence-based practices for scoping reviews following PRISMA-ScR, application of established guidelines for reporting with PRISMA-P, and the engagement of experts to ensure relevance and accuracy of results. Ultimately, the planned review will inform subsequent work to help translate the currently fragmented evidence base into an actionable framework grounded in practice-based expertise for researchers and state and local organizations to better understand and measure integrated pathways that shape economic mobility.

Data Availability Statement

The data supporting the current study are available in supplements posted in Open Science Framework at https://osf.io/f57h4/.

Acknowledgments

This project was funded by RTI International.