Walter Theseira
Biographic Data
| ID | 9094432 |
|---|---|
| NAME | Walter Theseira |
| GIVEN NAMES | Walter |
| FAMILY NAME | Theseira |
| SIGNATURE | THESEIRA W |
| AFFILIATIONS | Singapore University of Social Sciences |
| ORCID | 0000-0002-8738-2341 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 0 |
Pitfalls of self‐reported measures of self‐control
OBJECTIVE: We took a rare opportunity to examine whether extreme debtors have inflated assessment of their self-control capacity, potentially rendering self-reported measures ineffective as prediction tools for debt risks. METHOD: The self-control profiles of extreme debtors (n = 1442), whose credit card debt amounted to more than 12 months of their income, were compared with samples of the general population (n = 505) and students from an elite …
Evaluating human versus machine learning performance in classifying research abstracts
We study whether humans or machine learning (ML) classification models are better at classifying scientific research abstracts according to a fixed set of discipline groups. We recruit both undergraduate and postgraduate assistants for this task in separate stages, and compare their performance against the support vectors machine ML algorithm at classifying European Research Council Starting Grant project abstracts to their actual evaluation pane…
No prominent works on this page.
Evaluating human versus machine learning performance in classifying research abstracts
We study whether humans or machine learning (ML) classification models are better at classifying scientific research abstracts according to a fixed set of discipline groups. We recruit both undergraduate and postgraduate assistants for this task in separate stages, and compare their performance against the support vectors machine ML algorithm at classifying European Research Council Starting Grant project abstracts to their actual evaluation pane…
Pitfalls of self‐reported measures of self‐control
OBJECTIVE: We took a rare opportunity to examine whether extreme debtors have inflated assessment of their self-control capacity, potentially rendering self-reported measures ineffective as prediction tools for debt risks. METHOD: The self-control profiles of extreme debtors (n = 1442), whose credit card debt amounted to more than 12 months of their income, were compared with samples of the general population (n = 505) and students from an elite …
Psychology (2 works) · Advanced Text Analysis Techniques (1 works) · Artificial Intelligence (1 works) · Artificial Intelligence (1 works) · Behavioral Health and Interventions (1 works) · Biomedical Text Mining and Ontologies (1 works) · Clinical Psychology (1 works) · Computer Science (1 works) · Decision-Making and Behavioral Economics (1 works) · Developmental psychology (1 works)