Hear hear
11.01.2026 15:22 β π 0 π 0 π¬ 0 π 0Hear hear
11.01.2026 15:22 β π 0 π 0 π¬ 0 π 0Topics Please see below for a non-exhaustive list of suggested topics; we particularly welcome contributions that make contact with this year's conference theme: Ground Truth and Validity. While the notion of measurement validity is comparatively familiar, ground truth may need more of an introduction. The concept of ground truth has origins in remote sensing, where it is used to contrast the outcomes of a near or ground level measurement with outcomes of a remotely sensed measurement. From these origins, the concept has now moved to a wider use, particularly in machine learning contexts, where it denotes data assumed to be true, which can then be used to calibrate and validate machine learning data. The time seems ripe for a more careful investigation from a measurement perspective of the concept of ground truth-both in its original understanding and in its more metaphorical use. Measurement and Simulation β’ Connections between measuring and simulating β’ Can simulation substitute for measurement? Measurement and Data Science
Measurement and Data Science β’ Measurement and data quality β’ Measurement and data analysis β’ Measurement and Al Models in Measurement β’ The role of models in measurement β’ The role of models in justifying measurement results β’ Models, intersubjectivity, objectivity, validation Models of Measurement β’ The general structure of the measurement process β’ The structure of measurement in social and human sciences β’ Transduction and calibration in measurement β’ History of the conception of the structure of measurement History, Philosophy and Sociology of Measurement
The structure of measurement in social and human sciences β’ Transduction and calibration in measurement β’ History of the conception of the structure of measurement History, Philosophy and Sociology of Measurement β’ Exploration across sciences with diverse philosophical perspectives β’ New quantification and measurement approaches β’ Epistemological and metaphysical approaches to measurement Measurement Applications and their conceptual foundations in any area of science β’ Life & Health Sciences
CFP: Society for the Study of Measurement will be held at the University of Edinburgh
June 22-25, 2026. Submit proposals for papers, symposia, & poster on any topics in the theory, history, philosophy, & application of measurement by January 15, 2026 app.oxfordabstracts.com/stages/80364...
#HPS
New paper on adaptive sampling for ecological monitoring published in @oikosjournal.bsky.social nsojournals.onlinelibrary.wiley.com/doi/10.1002/.... Premise is to aim for proportional allocation across strata. Success depends on choice of stratifying variables. Oli Pescottβs brainchild
21.06.2025 10:32 β π 1 π 0 π¬ 0 π 0
Science-integrity project will root out bad medical papers βand tell everyoneβ
Thrilled to announce this new $900,000 project headed by @jamesheathers.bsky.social
Ecologistsβ endless quest for automatic inference
statmodeling.stat.columbia.edu/2025/05/28/e...
Our new paper combines wildlife surveillance data and spatial risk modelling to map suitability for TBEV in GB. We identified key drivers linked to TBEV exposure in deer and produced risk maps, which can guide future surveillance and interventions. www.eurosurveillance.org/content/10.2...
03.04.2025 17:15 β π 10 π 9 π¬ 1 π 1DAGs are nice way to think about sample selection biases, Ecology edition. besjournals.onlinelibrary.wiley.com/doi/10.1111/...
11.03.2025 19:42 β π 9 π 2 π¬ 1 π 0
It is only by understanding what causes sampling bias that we can correct it...
Check out our new Blog post by @robboyd.bsky.social here! π
https://buff.ly/3PVHA30
This paper just out using data from the UKBMS to demonstrate different ways to think about bias in datasets.
24.01.2025 08:39 β π 3 π 1 π¬ 0 π 0
πPublishedπ
Our new research article demonstrates how you might combine expert knowledge with causal diagrams and superpopulation models to mitigate geographic biases in biodiversity monitoring data π π§ͺ Read it here π
https://buff.ly/3C2ZKws
What have causal diagrams got to do with sampling bias? Find out here! Great team @richardfoxbc.bsky.social @davidroybrc.bsky.social + oli Pescott, Colin harrower, Emily Dennis, Ian middlebrook and Marc Botham. @ukceh.bsky.social @ukbms.bsky.social
22.01.2025 12:40 β π 6 π 1 π¬ 0 π 0
π¨ Interested in using #AI to help develop real-time early warnings of human-wildlife conflict?
Apply for a fully-funded #PhD supervised by Vicky Boult (University of Reading) and our own @robboyd.bsky.social
Part of the AI-INTERVENE programme. Deadline 27 Jan: www.findaphd.com/phds/project...
π‘ Can we use data science and AI to make citizen science more engaging for participants and improve biodiversity data quality?
π§ͺ Apply now for a competition-funded #PhD opportunity to explore - deadline 27 Jan.
www.findaphd.com/phds/project...
Still a couple of weeks left to apply for this #PhD. How are pollinating #insects changing in the UK? This project will develop indicators for #pollinators using #citizenscience data. A collaboration between @ukceh.bsky.social, University of Reading and JNCC. tinyurl.com/3ve5szrh
07.01.2025 11:16 β π 6 π 10 π¬ 0 π 0