Short Term Contract Opportunity (2 Contracts)

Position Summary

Short Term Contract Opportunity for Research Consultants
Global Knowledge Database

Start Date: May 12    Max End Date: July 15.

Fixed Price per contract: $23, 000 ($2000 performance-based incentive for successful and accepted completion by July 1, $1000 performance-based incentive for successful and accepted completion by July 8).

ReFED seeks two Qualitative Researchers to assist in a systematic review of Food Loss & Waste (FLW) Solutions across academic and non-academic qualitative content.

The researchers will be responsible for assisting in the use of Elicit – a platform for conducting systematic reviews – and analyzing academic article extracts to build a further refined structured excel file. Researchers will also assist in the analysis and synthesis of Elicit extracts to help answer key research questions.

Researchers will assist in all facets of project deliverables and report to a ReFED project lead who will provide guidance throughout the project. Experience with working with large unstructured data, qualitative analysis tools and techniques (e.g. LLM prompting, NLP), ontologies, as well as supply chains and impact evaluation metrics will all be a plus.

To apply, please submit required materials using this form by Wednesday May 7, 2025. Applications will be considered on a rolling basis until hires are made.

For questions please email .

Milestones
Milestone 1: Elicit queries and extractions completed.  Start by May 12 – Complete May 23 at latest

Milestone 2: Refinement of Elicit extractions and building of knowledge data set completed. Complete by June 15, 2025

Milestone 3: Analysis, Synthesis and Reporting on key findings that answer ReFED’s research questions completed. Complete by Jul 15, 2025 at the latest. A bonus of $2000 is offered for satisfactory work completion by July 1, or $1000 bonus for satisfactory work completion by July 8.

Deliverables
1.1 Run Elicit queries and store extractions as excel files following naming convention in requirement 1.1.a.

2.1 Meta data set that assigns each unique article in the knowledge base with a unique ID and extracts requisite features provided in requirement 2.1.a.

2.2 Analysis of the Elicit Extractions and refinement of findings into a structured data set with a view of answering key research questions defined in requirement 2.2.b.

3.1 Comprehensive report of findings that meets the requirements in 3.1.a.
3.2 Final project presentation detailing the report’s analytical methodology, findings, and recommendations with an opportunity of Q&A with stakeholders.

4. Periodic project status updates with ReFED’s manager and stakeholders to ensure continued alignment with stakeholder expectations.

Requirements

1.1.a) Name of Elicit Query_D.M.YY (eg On farm food loss_4.18.25).
2.1.a) We seek a structured approach to feature extraction and provide the following relational database of features to be built into multiple elicit queries on Food Waste and Loss Solutions across sectors, supply chain stages, and food types. While Elicit will conduct a preliminary process of curating sources and extracting features we define, researchers will be responsible for further refinement of Elicit outputs in the relational database of features and seeking answers to research questions.

2.2.a) Extracted features are expected to assist ReFED in addressing the following guiding research questions (each contractor will be assigned a unique set of features to extract and research questions to answer):

 

            2.2.a.i). Solution Classification

• What types of FLW solutions or interventions are most frequently cited across the literature?
• How are solutions mechanisms described and categorized (e.g., behavioral intervention, technological innovation, operational execution, physical infrastructure, policy)?

            2.2.a.ii).  Taxonomy

●      How are FLW solutions categorized across academic and industry sources (e.g., by intervention point, supply chain stage, root cause)?

●      How do these taxonomic dimensions converge or diverge from ReFED’s existing taxonomy?

●      Which classification approaches are most actionable for different audiences (e.g., businesses, policymakers)?

●      How might ReFED adapt or supplement its taxonomy to better reflect evolving practices or improve usability?

• Is there an implicit or explicit solution classification system to indicate a solution’s implementation readiness or level of solution implementation?

            2.2.a.iii). Sectors

• Which food system sectors (e.g., farm, manufacturing, retail, foodservice, residential) are most frequently associated with the cited solutions?
• Are any solutions explicitly designed to operate across multiple sectors? If so, how are cross-sectoral dynamics described (e.g., supply chain coordination, multi-actor roles)?
• Where are the key gaps in sectoral or subsectoral representation within the evidence base?
• How are subsectors within foodservice (non-institutional, e.g. full service restaurants, limited service restaurants) represented in the literature, and what solution types are most commonly applied to each?
• Which solutions exist to address food loss and waste at the consumer or household level? What mechanisms do these consumer/household-level solutions target (e.g., purchasing behavior, storage practices, meal planning)?
• Which solutions exist to address food loss occurring at the post-harvest stage on farms (e.g., storage, logistics, surplus management)? How do these post-harvest solutions differ from interventions aimed at farming practices or production methods?

2.2.a.iv). Causes

• What immediate and root causes of food loss and waste are most commonly cited across the literature?
  • Immediate cause = the direct, observable reason for the loss or waste event. Typically operational, technical, procedural, or action-based (ex: equipment failure, human error, poor inventory management, spoilage due to lack of refrigeration)
  • Root cause = the deeper systemic, behavioral, or structural reason underlying the occurrence of waste. Often linked to incentives, market structures, infrastructure gaps, policy frameworks, or cultural behaviors (ex: lack of infrastructure, supply chain power dynamics, consumer aesthetic standards)
• How do solutions explicitly or implicitly address these causes?
• Are there causes described in the literature that aren’t covered in ReFED’s existing taxonomy?

            2.2.a.v). Food Types

• What food types are most frequently associated with FLW solutions?
• How do traits like perishability or packaging affect which solutions are selected or how effective they are?

            2.2.a.vi). Functional Characteristics & Implementation Contexts

• What qualitative insights are provided about solution functionality, mechanisms, interdependencies, enabling conditions, and scalability?
• What external factors (e.g., geography, policy, operational constraints, culture) are cited as influencing solution adoption or effectiveness?
• Who are the actors involved in implementation (e.g., solution providers, funders, adopters), and what financing or cost-sharing models are mentioned?
• What, if any, evidence of phased solutions implementation exist in the literature (e.g. evidence for pilots, partial, and scaled deployments) and what can we learn from these for application for our own work?
• What are the necessary preconditions, precursors, interrelated factors, and order of operations that affect successful solution scaling?

                  2.2.a.vii). Quantitative Impacts and Methodologies

●      What quantitative impact estimates about solutions are most frequently reported in the literature (e.g. diversion or reduction potential, financial costs, financial benefits, environmental benefits, etc.), and how are they measured?

●      What units (e.g., pounds of food diverted/reduced, dollars, percent of FLW reduced) and timeframes are used to report outcomes?

• What assumptions, proxies, or formulas are used to estimate impacts?

●      Are there methodologies that estimate the proportion of edible vs. inedible waste in residential settings? If so, what values, units, and estimation methods are reported?

• Are there studies that discuss or model solutions’ payback periods?
• Are there studies that discuss or model solutions’ implementation timelines?

                  2.2.a.viii). Adoption & Market Penetration

●      To what extent is adoption or market penetration of solutions reported? Extract adoption metrics (e.g., number of sites, % penetration), the units of measure used, and the method of calculation.

●      What units and methods are used to describe adoption or penetration?

●      Who funds the solution, and what mechanisms (grants, subscriptions, PPPs) are cited?

●      Who are the implementing actors: providers, adopters, customers?

                  2.2.a.ix). Gaps & Opportunities

• What solutions are currently missing from ReFED’s Insights Engine appear in the literature and may warrant inclusion?
• Which unmodeled solutions in the literature have strong qualitative or partial evidence but lack full quantitative modeling?
• Where are the major evidence gaps across solution types, causes, geographies, or sectors that may require new research or data collection?

3.1.a). Synthesis of Findings

Researchers will assist in the completion of a final report. The final report will synthesize findings from Elicit extractions in alignment with ReFED’s research objectives and include the following elements:

• A detailed description of the methodology used for qualitative coding, metadata extraction, and synthesis, including any NLP models or systematic review frameworks applied. Clearly note how findings were validated and any limitations encountered.
• A dedicated section responding to each of the guiding research questions outlined in 2.2.a, including but not limited to:
• Solution classification and distinctions
• Taxonomic frameworks and comparison to ReFED’s current categorization
• Sectoral and subsectoral distribution of solutions
• Waste causes and their relationship to solution mechanisms
• Food types addressed and their intervention-specific characteristics
• Functional insights into mechanisms, enabling conditions, and context-specific factors
• Quantitative impact estimates and methods used to derive them
• Evidence of solution adoption, funding structures, and implementation stakeholders
• Key gaps and opportunities for further modeling or research
• Comparative analysis of ReFED’s current taxonomy versus taxonomies cited in the literature, as well as an assessment of which schema is the most operationally useful.
• A comparative analysis of ReFED’s current solution modeling methodologies (e.g., how financial, environmental, and diversion impacts are calculated) with those found in the literature, including:
• Units of measurement
• Calculation methods
• Assumptions and formulas used
• Limitations and opportunities for alignment or refinement
• Evidence-based recommendations for future research including:
  • New or underrepresented solutions for potential inclusion in ReFED’s Insights Engine
  • Methodological updates to improve consistency with emerging practices
  • Future research or data collection needs, particularly where the literature provides low-confidence or anecdotal insights