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Record W4200315954 · doi:10.1111/gean.12309

In memoriam: Martin Charlton

2021· article· en· W4200315954 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueGeographical Analysis · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicSpatial and Panel Data Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsBespokeRegional scienceGeographyCartographyNewcastle upon tyneLibrary scienceSociologyMedia studiesHistoryPolitical scienceArt historyComputer science

Abstract

fetched live from OpenAlex

Martin Edward Charlton (1957–2021) Martin Charlton was one of the leading pioneers of quantitative geography and geocomputation whose work helped inspire the recent resurgence of spatial analysis and geographic data science. He was born in Newcastle upon Tyne, where he attended the Royal Grammar School and subsequently the University of Newcastle upon Tyne, where he gained a First Class (Hons) degree in Town and Country Planning in 1978. After a short spell as a planner in Chichester, Martin returned to Newcastle University for the next 24 years, first registering as a PhD student with Stan Openshaw, then as a researcher in the Centre for Urban and Regional Development Studies, before achieving his first academic position as a Lecturer in the Department of Geography in 1991. In 2004, he cofounded the National Centre for Geocomputation at Maynooth University, Ireland where he remained until his retirement in 2020. Martin’s career spanned the (geo)computational revolution of the 1980s that resulted in the widespread use of computer programming for spatial analysis in geography leading to a core component of the current GIScience body of knowledge. His research was fundamental to many of the methodological innovations that are now central to the practice of quantitative geography: geodemographic classifications of census small area data, the creation of bespoke geographic information and mapping software, and a number of innovative spatial data analysis techniques. His research played a key role in two major contributions to the discipline: the Geographical Analysis Machine (GAM) in 1987 working with Stan Openshaw, Alan Craft, and many other collaborators, and Geographically Weighted Regression (GWR) in 1996 working with Stewart Fotheringham and Chris Brunsdon. Central to both the GAM and GWR was the idea of using innovative computational—and, critically, geocomputational—methods to explore and explain geographical patterns in data, moving away from “one size fits all” types of modeling applied uniformally across space, to focus on how outcomes and their causes vary across a map. Typically, Martin was responsible for the initial coding, frequently in Fortran and/or R, and the implementation of functions to undertake these operations, which were later developed into standalone tools and open source packages. Martin’s time spent at Newcastle spawned the widespread use of GAM and GWR, while at Maynooth, Martin developed a new small area geography for census dissemination, the expansion of the GWR methodology to a GW modeling paradigm and smart (programmable) city projects and dashboards. Martin has left us with a large and impressive body of research which currently stands at 22,000+ citations from 200+ publications. As well as considering his reputation in this metric-defined manner, with Martin we fondly remember his unique approach to academia. A memorable aspect of Martin’s talks was that, despite the content often relating to fairly abstract ideas in computing, statistics, or geographical data, there were always plenty of photographs to bring the subject to life and make it relevant to each and every member of the audience. These images were typically of people and places, and helped to tell the human story behind many of the ideas being discussed. For Martin these ideas were not purely mathematical abstractions, but concepts grounded in the people whose ideas they were, the motivations behind the ideas, and the places where the ideas were discussed. His work certainly contained complex mathematical ideas, but he was aware of the stories behind them, and made a place for their telling. This humanistic aspect was always of importance in his work. He would often remind us that the human geographical data we analyzed arose from the lives of people; in finding patterns we were understanding something deeper about these people, and hopefully influencing policies that would ultimately benefit them. Martin was an inspiring teacher. His lectures were entertaining and highly popular with students and he always made the time to help students struggling with the more difficult aspects of their studies, especially at dissertation submission time when the corridor outside his office would be lined by students waiting for Martin to patiently assist them with their geocomputational issues. This generosity with his time was extended to younger professional colleagues—we have heard many people recalling how he had helped them in their early careers, in some cases saying he was the very reason they became an academic in the first place. Martin was very much at home in his office—often 7 days a week—which again made him highly accessible. He thoroughly enjoyed applying geographical techniques to the wide range of research projects which his colleagues and students were grappling with. Hence, he has rather an eclectic mix of publications, ranging from cancer clustering through airborne LiDAR, to digital humanities. His work dealt with geographies as diverse as river channel dynamics in north Northumberland and the pyrogeography of sub-Saharan Africa. If there was a count of acknowledgments in dissertations, Martin’s metric would be extraordinary. Finally, we would like to remember Martin as our dear friend. Over many years, we have had numerous adventures together: writing books, giving talks, shifting pies, curries, and pints, and on at least one instance signing the Official Secrets Act. We traveled around the world, including visits to China, the United States, Canada, Australia, Japan, Brazil, and many European countries, and discussed ideas over a beer (actually rarely ‘a’ beer) in all of these places. In destinations with a cathedral or church, we would often accompany him to look at its organ, as Martin was a highly accomplished and passionate organist. However, even travels to places much closer to home were always a pleasure, thanks to the company he provided. Martin is missed not only as an excellent colleague but as our great friend and we are all the sorrier he was taken so early just as he should have set out to enjoy a full and well-earned retirement.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.165
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.007
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.215
Teacher spread0.195 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it