What Synthesis Methodology Should I Use? A Review and Analysis of Approaches to Research Synthesis.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: When we began this process, we were doctoral students and a faculty member in a research methods course. As students, we were facing a review of the literature for our dissertations. We encountered several different ways of conducting a review but were unable to locate any resources that synthesized all of the various synthesis methodologies. Our purpose is to present a comprehensive overview and assessment of the main approaches to research synthesis. We use 'research synthesis' as a broad overarching term to describe various approaches to combining, integrating, and synthesizing research findings. METHODS: We conducted an integrative review of the literature to explore the historical, contextual, and evolving nature of research synthesis. We searched five databases, reviewed websites of key organizations, hand-searched several journals, and examined relevant texts from the reference lists of the documents we had already obtained. RESULTS: We identified four broad categories of research synthesis methodology including conventional, quantitative, qualitative, and emerging syntheses. Each of the broad categories was compared to the others on the following: key characteristics, purpose, method, product, context, underlying assumptions, unit of analysis, strengths and limitations, and when to use each approach. CONCLUSIONS: The current state of research synthesis reflects significant advancements in emerging synthesis studies that integrate diverse data types and sources. New approaches to research synthesis provide a much broader range of review alternatives available to health and social science students and researchers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.130 | 0.102 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.001 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it