Elay Shech
Biographic Data
| ID | 1054776 |
|---|---|
| NAME | Elay Shech |
| GIVEN NAMES | Elay |
| FAMILY NAME | Shech |
| SIGNATURE | SHECH E |
| AFFILIATIONS | Auburn University |
| ORCID | 0000-0002-3863-5058 |
| VERIFIED | Yes |
| TOTAL WORKS | 19 |
| TOTAL CITATIONS | 49 |
| AUTHOR COUNT | 19 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2013 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 5 |
The Curve Fitting Problem, Data Validation, and Inductive Generalization in Machine Learning
Aris Spanos and Deborah Mayo’s error-statistical approach to statistical modeling and inference adopts the reliability of inductive inference as a primary criterion for statistical model and estimator selection (e.g., curve fitting). In this paper, we expand the error-statistical approach’s adoption of reliable inductive inference by scrutinizing the epistemic legitimacy of contemporary techniques leveraged in data science. We argue that data val…
The Mitonuclear Compatibility Species Concept, Intrinsic Essentialism, and Natural Kinds
This essay introduces, develops, and appraises the mitonuclear compatibility species concept (MCSC), identifying advantages and limitations with respect to alternative species concepts. While the consensus amongst most philosophers of biology is that (kind) essentialism about species is mistaken, and that species at most have relational essences, we appeal to the MCSC to defend thoroughgoing intrinsic essentialism. Namely, the doctrine that speci…
Bias, machine learning, and conceptual engineering
Large language models (LLMs) such as OpenAI’s ChatGPT reflect, and can potentially perpetuate, social biases in language use. Conceptual engineering aims to revise our concepts to eliminate such bias. We show how machine learning and conceptual engineering can be fruitfully brought together to offer new insights to both conceptual engineers and LLM designers. Specifically, we suggest that LLMs can be used to detect and expose bias in the prototyp…
Colors, Perceptual Variation, and Science
Inductive neutrality and scientific representation
Machine understanding and deep learning representation
Practical ability manifested through robust and reliable task performance, as well as information relevance and well-structured representation, are key factors indicative of understanding in the philosophical literature. We explore these factors in the context of deep learning, identifying prominent patterns in how the results of these algorithms represent information. While the estimation applications of modern neural networks do not qualify as …
Introduction to recent issues in philosophy of statistics: Evidence, testing, and applications
Idealization, representation, and explanation in the sciences
Scientific understanding in the Aharonov‐Bohm effect
By appealing to resources found in the scientific understanding literature, I identify in what senses idealisations afford understanding in the context of the (magnetic) Aharonov‐Bohm effect. Three types of concepts of understanding are discussed: understanding‐what, which has to do with understanding a phenomenon; understanding‐with, which has to do with understanding a scientific theory; and understanding‐why, which has to do with the reason so…
Scientific Understanding and Representation: Modeling in the Physical Sciences
Infinite idealizations in science: An introduction
Infinitesimal idealization, easy road nominalism, and fractional quantum statistics
Historical Inductions Meet the Material Theory
Historical inductions, that is, the pessimistic metainduction and the problem of unconceived alternatives, are critically analyzed via John D. Norton’s material theory of induction and subsequently rejected as noncogent arguments. It is suggested that the material theory is amenable to a local version of the pessimistic metainduction, for example, in the context of some medical studies
Idealizations, essential self-adjointness, and minimal model explanation in the Aharonov–Bohm effect
Infinite idealizations in physics
In this essay, I provide an overview of the debate on infinite and essential idealizations in physics. I will first present two ostensible examples: phase transitions and the Aharonov-Bohm effect. Then, I will describe the literature on the topic as a debate between two positions: Essentialists claim that idealizations are essential or indispensable for scientific accounts of certain physical phenomena, while dispensabilists maintain that idealiz…
Teaching and Learning Guide for: Infinite idealizations in physics
Scientific misrepresentation and guides to ontology: The need for representational code and contents
On Gases in Boxes: A Reply to Davey on the Justification of the Probability Measure in Boltzmannian Statistical Mechanics
Kevin Davey claims that the justification of the second law of thermodynamics as it is conveyed by the “standard story” of statistical mechanics, roughly speaking, that low-entropy microstates tend to evolve to high-entropy microstates, is “unhelpful at best and wrong at worst.” In reply, I demonstrate that Davey’s argument for rejecting the standard story commits him to a form of skepticism that is more radical than the position he claims to be …
What Is the Paradox of Phase Transitions
I present a novel approach to the scholarly debate that has arisen with respect to the philosophical import one should infer from scientific accounts of phase transitions by appealing to a distinction between representation understood as denotation, and faithful representation understood as a type of guide to ontology. It is argued that the entire debate is misguided, for it stems from a pseudo-paradox that does not license the type of claims mad…
What Is the Paradox of Phase Transitions
I present a novel approach to the scholarly debate that has arisen with respect to the philosophical import one should infer from scientific accounts of phase transitions by appealing to a distinction between representation understood as denotation, and faithful representation understood as a type of guide to ontology. It is argued that the entire debate is misguided, for it stems from a pseudo-paradox that does not license the type of claims mad…
Scientific misrepresentation and guides to ontology: The need for representational code and contents
Idealizations, essential self-adjointness, and minimal model explanation in the Aharonov–Bohm effect
Infinite idealizations in physics
In this essay, I provide an overview of the debate on infinite and essential idealizations in physics. I will first present two ostensible examples: phase transitions and the Aharonov-Bohm effect. Then, I will describe the literature on the topic as a debate between two positions: Essentialists claim that idealizations are essential or indispensable for scientific accounts of certain physical phenomena, while dispensabilists maintain that idealiz…
Infinite idealizations in science: An introduction
Infinitesimal idealization, easy road nominalism, and fractional quantum statistics
Bias, machine learning, and conceptual engineering
Large language models (LLMs) such as OpenAI’s ChatGPT reflect, and can potentially perpetuate, social biases in language use. Conceptual engineering aims to revise our concepts to eliminate such bias. We show how machine learning and conceptual engineering can be fruitfully brought together to offer new insights to both conceptual engineers and LLM designers. Specifically, we suggest that LLMs can be used to detect and expose bias in the prototyp…
Machine understanding and deep learning representation
Practical ability manifested through robust and reliable task performance, as well as information relevance and well-structured representation, are key factors indicative of understanding in the philosophical literature. We explore these factors in the context of deep learning, identifying prominent patterns in how the results of these algorithms represent information. While the estimation applications of modern neural networks do not qualify as …
Idealization, representation, and explanation in the sciences
Historical Inductions Meet the Material Theory
Historical inductions, that is, the pessimistic metainduction and the problem of unconceived alternatives, are critically analyzed via John D. Norton’s material theory of induction and subsequently rejected as noncogent arguments. It is suggested that the material theory is amenable to a local version of the pessimistic metainduction, for example, in the context of some medical studies
On Gases in Boxes: A Reply to Davey on the Justification of the Probability Measure in Boltzmannian Statistical Mechanics
Kevin Davey claims that the justification of the second law of thermodynamics as it is conveyed by the “standard story” of statistical mechanics, roughly speaking, that low-entropy microstates tend to evolve to high-entropy microstates, is “unhelpful at best and wrong at worst.” In reply, I demonstrate that Davey’s argument for rejecting the standard story commits him to a form of skepticism that is more radical than the position he claims to be …
What Is the Paradox of Phase Transitions
I present a novel approach to the scholarly debate that has arisen with respect to the philosophical import one should infer from scientific accounts of phase transitions by appealing to a distinction between representation understood as denotation, and faithful representation understood as a type of guide to ontology. It is argued that the entire debate is misguided, for it stems from a pseudo-paradox that does not license the type of claims mad…
Scientific misrepresentation and guides to ontology: The need for representational code and contents
Idealizations, essential self-adjointness, and minimal model explanation in the Aharonov–Bohm effect
Infinite idealizations in physics
In this essay, I provide an overview of the debate on infinite and essential idealizations in physics. I will first present two ostensible examples: phase transitions and the Aharonov-Bohm effect. Then, I will describe the literature on the topic as a debate between two positions: Essentialists claim that idealizations are essential or indispensable for scientific accounts of certain physical phenomena, while dispensabilists maintain that idealiz…
Teaching and Learning Guide for: Infinite idealizations in physics
Infinite idealizations in science: An introduction
Infinitesimal idealization, easy road nominalism, and fractional quantum statistics
Historical Inductions Meet the Material Theory
Historical inductions, that is, the pessimistic metainduction and the problem of unconceived alternatives, are critically analyzed via John D. Norton’s material theory of induction and subsequently rejected as noncogent arguments. It is suggested that the material theory is amenable to a local version of the pessimistic metainduction, for example, in the context of some medical studies
Scientific understanding in the Aharonov‐Bohm effect
By appealing to resources found in the scientific understanding literature, I identify in what senses idealisations afford understanding in the context of the (magnetic) Aharonov‐Bohm effect. Three types of concepts of understanding are discussed: understanding‐what, which has to do with understanding a phenomenon; understanding‐with, which has to do with understanding a scientific theory; and understanding‐why, which has to do with the reason so…
Scientific Understanding and Representation: Modeling in the Physical Sciences
Inductive neutrality and scientific representation
Machine understanding and deep learning representation
Practical ability manifested through robust and reliable task performance, as well as information relevance and well-structured representation, are key factors indicative of understanding in the philosophical literature. We explore these factors in the context of deep learning, identifying prominent patterns in how the results of these algorithms represent information. While the estimation applications of modern neural networks do not qualify as …
Introduction to recent issues in philosophy of statistics: Evidence, testing, and applications
Idealization, representation, and explanation in the sciences
Colors, Perceptual Variation, and Science
The Curve Fitting Problem, Data Validation, and Inductive Generalization in Machine Learning
Aris Spanos and Deborah Mayo’s error-statistical approach to statistical modeling and inference adopts the reliability of inductive inference as a primary criterion for statistical model and estimator selection (e.g., curve fitting). In this paper, we expand the error-statistical approach’s adoption of reliable inductive inference by scrutinizing the epistemic legitimacy of contemporary techniques leveraged in data science. We argue that data val…
The Mitonuclear Compatibility Species Concept, Intrinsic Essentialism, and Natural Kinds
This essay introduces, develops, and appraises the mitonuclear compatibility species concept (MCSC), identifying advantages and limitations with respect to alternative species concepts. While the consensus amongst most philosophers of biology is that (kind) essentialism about species is mistaken, and that species at most have relational essences, we appeal to the MCSC to defend thoroughgoing intrinsic essentialism. Namely, the doctrine that speci…
Bias, machine learning, and conceptual engineering
Large language models (LLMs) such as OpenAI’s ChatGPT reflect, and can potentially perpetuate, social biases in language use. Conceptual engineering aims to revise our concepts to eliminate such bias. We show how machine learning and conceptual engineering can be fruitfully brought together to offer new insights to both conceptual engineers and LLM designers. Specifically, we suggest that LLMs can be used to detect and expose bias in the prototyp…
Epistemology (18 works) · Philosophy (18 works) · Philosophy and History of Science (12 works) · Computer Science (10 works) · Philosophy of science (9 works) · Metaphysics (8 works) · Philosophy of language (8 works) · Physics (6 works) · Mathematics (5 works) · Quantum Mechanics and Applications (5 works)