A presente dissertação tem o objetivo apresentar e refletir o modo como a metateoria estruturalista realiza análises filosófico-metacientíficas. Tal empreitada manterá o foco principal na relação entre teoria científica e experimento. Isto nos permitirá o embate com questões cruciais à filosofia da ciência, tais como a impregnação teórica do teste empírico e a distinção teórico/observacional. Tanto no decorrer quanto ao cabo de nossas reflexões ficará claro o avanço promovido pela metateoria estruturalista no que diz respeito à riqueza de análises metacientíficas possibilitadas pelo seu aparato conceitual. / The purpose of this dissertation is to present and reflect on how the structuralist metatheory performs metaphysical-philosophical analysis. This endeavor will maintain the main focus on the relationship between scientific theory and experiment. This will allow us to tackle issues crucial to the philosophy of science, such as the theoretical impregnation of the empirical test and the theoretical /observational distinction. Both in the course and in the end of our reflections will be clear the advance promoted by the structuralist metatheory with respect to the wealth of metascientific analyzes made possible by its conceptual apparatus.

A presente dissertação tem o objetivo apresentar e refletir o modo como a metateoria estruturalista realiza análises filosófico-metacientíficas. Tal empreitada manterá o foco principal na relação entre teoria científica e experimento. Isto nos permitirá o embate com questões cruciais à filosofia da ciência, tais como a impregnação teórica do teste empírico e a distinção teórico/observacional. Tanto no decorrer quanto ao cabo de nossas reflexões ficará claro o avanço promovido pela metateoria estruturalista no que diz respeito à riqueza de análises metacientíficas possibilitadas pelo seu aparato conceitual. / The purpose of this dissertation is to present and reflect on how the structuralist metatheory performs metaphysical-philosophical analysis. This endeavor will maintain the main focus on the relationship between scientific theory and experiment. This will allow us to tackle issues crucial to the philosophy of science, such as the theoretical impregnation of the empirical test and the theoretical /observational distinction. Both in the course and in the end of our reflections will be clear the advance promoted by the structuralist metatheory with respect to the wealth of metascientific analyzes made possible by its conceptual apparatus.

abstract: Science is a formalized method for acquiring information about the world. In recent years, the ability of science to do so has been scrutinized. Attempts to reproduce findings in diverse fields demonstrate that many results are unreliable and do not generalize across contexts. In response to these concerns, many proposals for reform have emerged. Although promising, such reforms have not addressed all aspects of scientific practice. In the social sciences, two such aspects are the diversity of study participants and incentive structures. Most efforts to improve scientific practice focus on replicability, but sidestep issues of generalizability. And while researchers have speculated about the effects of incentive structures, there is little systematic study of these hypotheses. This dissertation takes one step towards filling these gaps. Chapter 1 presents a cross-cultural study of social discounting – the purportedly fundamental human tendency to sacrifice more for socially-close individuals – conducted among three diverse populations (U.S., rural Indonesia, rural Bangladesh). This study finds no independent effect of social distance on generosity among Indonesian and Bangladeshi participants, providing evidence against the hypothesis that social discounting is universal. It also illustrates the importance of studying diverse human populations for developing generalizable theories of human nature. Chapter 2 presents a laboratory experiment with undergraduates to test the effect of incentive structures on research accuracy, in an instantiation of the scientific process where the key decision is how much data to collect before submitting one’s findings. The results demonstrate that rewarding novel findings causes respondents to make guesses with less information, thereby reducing their accuracy. Chapter 3 presents an evolutionary agent-based model that tests the effect of competition for novel findings on the sample size of studies that researchers conduct. This model demonstrates that competition for novelty causes the cultural evolution of research with smaller sample sizes and lower statistical power. However, increasing the startup costs to conducting single studies can reduce the negative effects of competition, as can rewarding publication of secondary findings. These combined chapters provide evidence that aspects of current scientific practice may be detrimental to the reliability and generalizability of research and point to potential solutions. / Dissertation/Thesis / Doctoral Dissertation Anthropology 2018

Yes / In recent years, there has been a focus in social psychology on efforts to improve the robustness, rigour, transparency and openness of psychological research. This has led to a plethora of new tools, practices and initiatives that each aim to combat questionable research practices and improve the credibility of social psychological scholarship. However, the majority of these efforts derive from quantitative, deductive, hypothesis-testing methodologies, and there has been a notable lack of in-depth exploration about what the tools, practices and values may mean for research that uses qualitative methodologies. Here, we introduce a Special Section of BJSP: Open Science, Qualitative Methods and Social Psychology: Possibilities and Tensions. The authors critically discuss a range of issues, including authorship, data sharing and broader research practices. Taken together, these papers urge the discipline to carefully consider the ontological, epistemological and methodological underpinnings of efforts to improve psychological science, and advocate for a critical appreciation of how mainstream open science discourse may (or may not) be compatible with the goals of qualitative research.

Metabolomics is the study of metabolites and metabolic processes. Due to the diversity of structures and polarities of metabolites, no single analytical technique is able to measure the entire metabolome - instead a varied set of experimental designs and instrumental technologies are used to measure specific portions. This has led to the development of many distinct data analysis and processing methods and software. There is hope that metabolomics can be utilized for clinical applications, in toxicology and to measure the exposome. However, for these applications to be realised data must be high quality, sufficiently standardised and annotated, and FAIR (Findable, Accessible, Interoperable and Reproducible). For this purpose, it is also important that standardised, FAIR software workflows are available. There has also recently been much concern over the reproducibility of scientific research, which FAIR and open data, and workflows can help to address. To this end, this thesis aims to assess current practices and standards of sharing data within the field of metabolomics, using metascientific approaches. The types of functions of software for processing and analysing metabolomics data is also assessed. Reporting standards are designed to ensure that the minimum information required to un- derstand and interpret the results of analysis are reported. However, poor reporting standards are ignored and not complied with. Compliance to the biological context Metabolomics Standards Initiative (MSI) guidelines was examined, in order to investigate their timeliness. The state of open data within the metabolomics community was examined by investigating how much publicly available metabolomics data there is and where has it been deposited. To explore whether journal data sharing policies are driving open metabolomics data, which journals publish articles that have their underlying data made open was also examined. However, open data alone is not inherently useful: if data is incomplete, lacking in quality or missing crucial metadata, it is not valuable. Conversely, if data are reused, this can demonstrate the worth of public data archiving. Levels of reuse of public metabolomics data were therefore examined. With greater than 250 software tools specific for metabolomics, practitioners are faced with a daunting task to select the best tools for data collection and analysis. To help educate researchers about what software is available, a taxonomy of metabolomics software tools and a GitHub pages wiki, which provides extensive details about all included software, have been developed.