Knowledge from Non-Knowledge

Luzzi, Federico

doi:10.1017/9781108649278

Cited by 11 publications

(5 citation statements)

References 152 publications

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“…From an epistemological (i.e. how we develop knowledge) standpoint, Luzzi (2019) argued that individuals could draw inferences based on false knowledge or mere ignorance, thereby generating erroneous or implausible knowledge about a particular phenomenon. Therefore, identifying knowledge-based inferences when analyzing data in MMR and preparing to generate metainferences is necessary to make appropriate comparisons and linkages between these types of inferences, and experience-based and data-driven inferences, as well as to reduce the likelihood of generating biased metainferences about a particular topic.…”

Section: Process To Generating Metainferences In Convergent Mixed Met...mentioning

confidence: 99%

Generating metainferences in mixed methods research: A worked example in convergent mixed methods designs

Younas

Fàbregues

Creswell

2023

Methodological Innovations

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Metainferences, or the insights derived from integrating quantitative and qualitative inferences at the end of a study, are crucial for achieving added value and synergy in mixed methods research. There is an ongoing need to understand how researchers generate metainferences, especially considering their pivotal role in helping researchers achieve full quantitative and qualitative integration. While some examples of metainferences generation are available in the mixed methods literature, more explicit guidance is required. Approaches to developing metainferences must also be contextual, as inferences of this type are contingent on the nature and purpose of the mixed methods study, the type of mixed methods design, and the quality of the research data. This paper describes a seven-step process for generating metainferences using a convergent mixed methods study as an exemplar. These steps consist of identifying knowledge, experience, and data-driven inferences from the quantitative and qualitative data; developing inference association maps to draw metainferences; and assessing the validity of metainferences using backward working heuristics. This paper contributes to mixed methods research by shedding light on the development of metainferences in convergent designs and by providing practical and tangible tools for making sense of the complexity of the analysis and interpretation tasks involved in the process of generating metainferences.

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Section: Process To Generating Metainferences In Convergent Mixed Met...mentioning

confidence: 99%

Generating metainferences in mixed methods research: A worked example in convergent mixed methods designs

Younas

Fàbregues

Creswell

2023

Methodological Innovations

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“…10 Essas teses impossibilitam também a obtenção de conhecimento inferencial a partir de crença gettierizada e de crença injustificada, por exemplo. Para mais informações, veja Luzzi (2014Luzzi ( , 2019, Olivier (2019), Murphy (2017). 11 Embora possa haver casos nos quais uma crença verdadeira e uma crença falsa, independentes entre si, sejam os fatores causais e evidenciais de uma outra crença verdadeira que é uma instância de conhecimento, perceba que esse tipo de caso não é um contraexemplo ao princípio CFC.…”

Section: Contrafecho Do Conhecimento (Cfc)unclassified

“…O objetivo dessa metodologia é empregar as ferramentas das ciências empíricas -como a ciência cognitiva, por exemplo -para avaliar a interpretação do senso comum de teses filosóficas e se essas interpretações são compatíveis com a teorização filosófica. Para mais informações, veja, respectivamente, Knobe e Nichols (2017) e Williamson (2018).15 Essa ideia de estabilidade da crença verdadeira derivada da crença falsa é melhor desenvolvida porLuzzi (2019).…”

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Restaurando a Explicação do Anulabilismo Falibilista sobre o Conhecimento a partir de Crença Falsa

Alves

2021

Intuitio

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O objetivo deste artigo é responder a duas objeções que podem ser feitas à explicação do anulabilismo falibilista referente à possibilidade de conhecimento inferencial originado em falsidade (KFF). A primeira objeção é que a ausência de restauradores indica a incompletude da explicação anulabilista falibilista de KFF, enquanto a segunda é que o experimento mental de KFF viola o Princípio Resistência à Verdade* (RV*) — a principal tese do anulabilismo falibilista. Na primeira seção, explicarei no que consiste o debate acerca da possibilidade de conhecimento inferencial a partir de falsidade; na segunda seção, explicarei o anulabilismo falibilista, desenvolvida por de Almeida (2017); na última seção, desenvolverei os argumentos que podem ser feitos contra o anulabilismo falibilista e explicarei por que não funcionam.

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“…28 See Saunders and Champawat (1964), Hilpinen (1988), Klein (1996Klein ( : 106, 2008, Hawthorne (2004: 57), Warfield (2005), Coffman (2008), Fitelson (2010Fitelson ( , 2017, Feit and Cullison (2011), Arnold (2013), Hiller (2013), de Almeida (2017), Hawthorne and Rabinowitz (2017), Buford and Cloos (2018), Turri (2019), Luzzi (2019), Zhao (Forthcoming).…”

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confidence: 99%

First-Class and Coach-Class Knowledge

Paulson

2023

Episteme

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I will discuss a variety of cases such that the subject's believing truly is somewhat of an accident, but less so than in a Gettier case. In each case, this is because her reasons are not ultimately undefeated full stop, but they are ultimately undefeated with certain qualifications. For example, the subject's reasons might be ultimately defeated considered in themselves but ultimately undefeated considered as a proper part of an inference to the best explanation that is undefeated without qualification. In each section of the paper, I consider different qualifications and show how in each case we get an epistemic standing I call “coach-class knowledge”. First-class knowledge requires justifying reasons that are undefeated without qualification. Coach-class knowledge only requires qualified lack of defeat. I will use this distinction to bring debates over knowledge from falsehood and fake barns to an ecumenical resolution. In both cases, the subject enjoys coach-class rather than first-class knowledge. I will also show that the defeasible reasoning tradition can better account for graded accidental truth than safety theories.

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Knowledge from Non-Knowledge

Cited by 11 publications

References 152 publications

Generating metainferences in mixed methods research: A worked example in convergent mixed methods designs

Generating metainferences in mixed methods research: A worked example in convergent mixed methods designs

Restaurando a Explicação do Anulabilismo Falibilista sobre o Conhecimento a partir de Crença Falsa

First-Class and Coach-Class Knowledge

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