Oct 2026· Journal of Intelligence· 0 citations· 34 references
Psychometric Methodologies and Testing
Abstract
Large-scale surveys often use cognitive test total scores to describe group differences, but the construct meaning of such scores depends on task content, administration, language experience, and opportunities to learn. The China Family Panel Studies (CFPS) word test is an oral Mandarin character reading task with education-dependent entry and stopping rules. We analyzed 16,689 adults followed from 2010 to 2018 using the full survey strata, primary sampling units, and longitudinal weights, and contrasted baseline-adjusted, gain score, geographic overlap, propensity overlap, floor exclusion, nonlinear, and measurement error sensitivity results. The fully adjusted 2018 contrast relative to Mandarin-speaking homes was −0.023 SD (95% CI [−0.077, 0.030]) for Sinitic-dialect homes and −0.292 SD (95% CI [−0.430, −0.154]) for the pooled minority-language response category. The latter estimate was reduced to −0.183 SD after exact ethnicity code fixed effects and to −0.081 SD (95% CI [−0.291, 0.129]) under overlap weighting; only 49 respondents fell in the 1st–99th percentile propensity score intersection. A covariate-adjusted gain score model yielded a smaller minority-language contrast (−0.180 SD, 95% CI [−0.356, −0.005]). Correcting the baseline under plausible reliability values of 0.85–0.95 produced point estimates from −0.226 to −0.277 SD. Floor exclusions reduced but did not eliminate the negative contrast. These results show that the pooled minority-language coefficient is strongly estimand- and support-dependent. They support a constrained interpretation of the observed CFPS score rather than a direct inference about broad crystallized intelligence or a uniform effect of minority-language use.
Supporting data, adapters, predictions and code for the article *Low-Cost LoRA Fine-Tuning of Small Language Models for Multi-Step Arithmetic Reasoning* by Jake O'Grady, Asena Isik Gürhan, Chee Fong Ting and Effirul Ramlan (University of Galway). We generated 20,000 GSM8K-derived arithmetic problems with step-by-step s...
O'Grady, Jake, Gürhan, Asena Isik, Chee, Fong Ting et al.· Zenodo (CERN European Organi...· 465 citations
The results are packaged in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible, and the need to shorten time-to-market, by speeding up the development through low-precision engineering activities.
Carmine Giardino, Nicolò Paternoster, M. Unterkalmsteiner et al.· IEEE Transactions on Softwar...· 178 citations· ⚡14
Software startup companies develop innovative, software-intensive products within limited timeframes and with few resources, searching for sustainable and scalable business models.
M. Unterkalmsteiner, P. Abrahamsson, Xiaofeng Wang et al.· e-Informatica Software Engin...· 157 citations· ⚡17
This study conducts a case survey study based on the secondary data of the major pivots happened in 49 software startups, and demonstrates that customer need pivot is the most common among all pivot types.
Sohaib Shahid Bajwa, Xiaofeng Wang, Anh Nguyen-Duc et al.· Empirical Software Engineeri...· 127 citations· ⚡15
The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.
Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al.· Journal of Systems and Softw...· 111 citations· ⚡8
The ongoing work building a Raspberry Pi cluster consisting of 300 nodes is presented, with potential use cases being an inexpensive and green test bed for cloud computing research and a robust and mobile data center for operating in adverse environments.
P. Abrahamsson, S. Helmer, Nattakarn Phaphoom et al.· IEEE International Conferenc...· 110 citations· ⚡7
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Microsoft Research Blog· microsoft.comOct 15, 2026
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.