In qualitative research, the concept of “data saturation” is often cited as a justification for sample size and cessation of data collection. Yet, far too many researchers treat saturation as a magic number — often 12 or 15 interviews — based on citations taken out of context, without deep engagement with the analytical logic behind … Read more
In an academic world increasingly pushing for “interdisciplinary” work, many researchers have begun to frame their studies as such — often without realizing what true interdisciplinarity actually demands. At Research & Report, we frequently encounter manuscripts that use keywords like climate + finance, AI + governance, or health + education, only to find that the … Read more
In recent years, the global research community has made strides in promoting open science, equitable access, and inclusivity. But beneath these visible reforms lies an invisible yet powerful gatekeeper that continues to marginalize voices and distort knowledge flows: language bias in academic publishing. At Research & Report, we routinely work with brilliant scholars — particularly … Read more
In qualitative research, validity is not merely technical — it is deeply interpretive, ethical, and relational. Yet, while researchers meticulously detail methods, tools, and coding frameworks, they often gloss over or omit a critical component: positionality and reflexivity. This oversight undermines not only the credibility of the study but also its epistemological integrity. At Research … Read more
In academic and applied research circles, the terms scoping and exploratory often carry an unintended implication: that the work is preliminary, informal, or exempt from rigor. That’s a dangerous myth. At Research & Report, we frequently observe a pattern: researchers use the label “exploratory” to excuse vague questions, ad-hoc methods, or weak analytical structure — … Read more
Time-series models are among the most powerful tools in empirical research — used to forecast trends, evaluate policy impacts, and assess long-term relationships across economics, finance, climate, and public policy. But too often, researchers focus on sophisticated modeling techniques (like ARDL, VAR, or VECM) without laying the proper statistical foundation.The result? Spurious regressions, invalid inferences, … Read more
In quantitative research, justifying sample size is a fundamental requirement. Yet, one of the most misused tools in this process is G*Power — a free and powerful program that helps estimate sample sizes based on power analysis.While G*Power is valuable, it’s often misapplied or overly relied upon, leading to flawed research designs, underpowered studies, and … Read more
Despite the growing acceptance and institutionalization of qualitative research in academia, many studies still fall into a critical trap — they lack a solid theoretical foundation. While qualitative methods are celebrated for exploring complexity, meaning, and lived experience, they are increasingly being used in ways that are conceptually shallow, methodologically misaligned, and analytically weak. This … Read more
Regression analysis is one of the most widely used statistical tools in empirical research. Yet, beneath many published models lies a silent killer of validity: the misuse of control variables. Too often, researchers include controls reflexively — without a clear understanding of their role in causal inference or model integrity. This article dives into what … Read more
In an era of publish-or-perish, identifying a “research gap” has become a standard ritual in academic writing. Yet, most so-called gaps are superficial at best — and misleading at worst. A weak gap leads to weak contribution. And this is where most researchers, including many doctoral candidates and early-career academics, unknowingly undermine their own work. … Read more
