Evidence-Based Practice in the social sciences? A scale of causality, interventions, and possibilities for scientific proof

Tellings, Agnes

doi:10.1177/0959354317726876

Cited by 12 publications

(8 citation statements)

References 27 publications

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“…Thus, the proposals put forward here cannot be proved as mathematical theorems. There may be exceptions, and indeed there are logics not revealed by the present analysis (Tellings, 2017). At the same time, the present analysis suggests new and significant directions of inquiry.…”

Section: Explaining Mind–world Relationsmentioning

confidence: 58%

The limits of language as the limits of psychological explanation

Gergen

2018

Theory & Psychology

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Extending early work on the limits of hypothesis testing, I propose that psychological explanations for behavior draw their intelligibility from tautology. A reliance on tautology is born of the impossibility for ostensively defining the explanans (e.g., the state of mind presumably giving rise to action). Thus, one makes psychological sense by explaining a given behavior in terms of a "miniaturized" form of itself. Further, because each definition of a mental term relies on another mental term for its meaning, we enter a condition of unbridled diffusion of definition. We may thus account for psychological explanations far removed from simple or transparent tautology. Through extended definitional sequences, we find that any given behavior can be explained by virtually any randomly drawn motive or trait. This includes otherwise counter-intuitive or paradoxical explanations. These developments bear importantly on the grounding assumptions for psychological research, mental and diagnostic testing, and psychotherapy.

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Section: Explaining Mind–world Relationsmentioning

confidence: 58%

The limits of language as the limits of psychological explanation

Gergen

2018

Theory & Psychology

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“…For both of these reasons, it is important for further research to dissect more precisely the understanding of the word “cause” that is triggered when students see explanation accompanying the presentation of a statistical association. In the social sciences, there is a concept of sufficient motive causality that describes how belief in a causal relationship can be substantiated by explaining why a sufficient set of motives could have led to a result ( Tellings, 2017 ). For example, this type of reasoning is used by historians to understand why certain events occurred.…”

Section: Discussionmentioning

confidence: 99%

Explanation of observational data engenders a causal belief about smoking and cancer

Myint

Leek

Jager

2018

PeerJ

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Most researchers do not deliberately claim causal results in an observational study. But do we lead our readers to draw a causal conclusion unintentionally by explaining why significant correlations and relationships may exist? Here we perform a randomized controlled experiment in a massive open online course run in 2013 that teaches data analysis concepts to test the hypothesis that explaining an analysis will lead readers to interpret an inferential analysis as causal. We test this hypothesis with a single example of an observational study on the relationship between smoking and cancer. We show that adding an explanation to the description of an inferential analysis leads to a 15.2% increase in readers interpreting the analysis as causal (95% confidence interval for difference in two proportions: 12.8%–17.5%). We then replicate this finding in a second large scale massive open online course. Nearly every scientific study, regardless of the study design, includes an explanation for observed effects. Our results suggest that these explanations may be misleading to the audience of these data analyses and that qualification of explanations could be a useful avenue of exploration in future research to counteract the problem. Our results invite many opportunities for further research to broaden the scope of these findings beyond the single smoking-cancer example examined here.

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“…Kvernbekk (2011, p. 532) explains evidence as the degree of effectiveness of strategies or interventions, or, “the truth-value of our claims about such effectiveness” and that its function is to support, confirm or disconfirm, a hypothesis or theory. As Tellings (2017, p. 584) explains, “evidence” is not the same as “proof.” The “Grades of Recommendation, Assessment, Development, and Evaluation” offers five major areas or domains to assess the quality of evidence proposed in the literature: issues with the study design or execution, inconsistency of results, indirectness of evidence, imprecision of results and publication bias (Pandis et al , 2015).…”

Section: Introductionmentioning

confidence: 99%

An evidence-based urban DRR strategy for informal settlements

Sarmiento

Polak

Sandoval

2019

DPM

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Purpose-The purpose of this paper is to analyze the evidence-based research strategy (EBRS) used to evaluate eight projects that applied the neighborhood approach for disaster risk reduction (NA-DRR) in informal urban settlements in Colombia, Guatemala, Haiti, Honduras, Jamaica and Peru, between 2012 and 2017. Design/methodology/approach-The study covers the first five of the seven EBRS stages: first, identify relevant interventions; second, prepare evaluation questions; third, select evidence sources and implement a search strategy; fourth, appraise evidences and identify gaps; fifth, create an evaluation design to include an extensive literature review, followed by a mixed research method with surveys, focus groups and interviews; disaster risk modeling; georeferencing analysis; and engineering inspections. The last two stages: sixth, apply the evidence, and seventh, evaluate the evidence application, will be addressed in a near future. Findings-Even though the reference to "evidence" is frequent in the DRR field, it is largely based on descriptive processes, anecdotal references, best practices, lessons learned and case studies, and particularly deficient on the subject of informal and precariousness settlements. The evaluation allowed a deep and broad analysis of NA-DRR in urban informal settlements, comparing it with other DRR strategies implemented by different stakeholders in fragile urban settings, assessing the effectiveness and sustainability of the various DRR interventions. Originality/value-The abundant data, information and knowledge generated will serve as foundation for forthcoming thematic peer-reviewed publications informing evidence-based DRR research, policy and practice, with emphasis on informal and precariousness settlements in particular.

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Evidence-Based Practice in the social sciences? A scale of causality, interventions, and possibilities for scientific proof

Cited by 12 publications

References 27 publications

The limits of language as the limits of psychological explanation

The limits of language as the limits of psychological explanation

Explanation of observational data engenders a causal belief about smoking and cancer

An evidence-based urban DRR strategy for informal settlements

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