Collapsing Waste Fractions Without Reducing Sorting Accuracy
Wrisberg, Anton LU
; Wallin, Annika
LU
and Pärnamets, Philip
(2026)
- Abstract
- Waste sorting signs present an inviting avenue for comparison of categorisation theories as they often contain both a rule and either an abstract prototype or visual exemplars. Focus in waste sorting studies is often on increasing the number of waste fractions, but some public settings might require fewer-than-ordinary fractions. This paper investigates two approaches to reducing a waste sorting system’s granularity at a music festival: explicit combining waste fractions by merging waste signs and implicitly combining fractions by removing alternatives to ‘residual waste’. The digital sorting results are modelled as a probit regression allowing direct interpretation in terms of signal detection theory’s senstitivy and criterion parameters.... (More)
- Waste sorting signs present an inviting avenue for comparison of categorisation theories as they often contain both a rule and either an abstract prototype or visual exemplars. Focus in waste sorting studies is often on increasing the number of waste fractions, but some public settings might require fewer-than-ordinary fractions. This paper investigates two approaches to reducing a waste sorting system’s granularity at a music festival: explicit combining waste fractions by merging waste signs and implicitly combining fractions by removing alternatives to ‘residual waste’. The digital sorting results are modelled as a probit regression allowing direct interpretation in terms of signal detection theory’s senstitivy and criterion parameters. The paper further compares four alternative waste sorting signs including visual exemplars to improve waste sorting accuracy for the implicitly combined waste fraction. The results suggest that explicitly combining waste fractions outperform implicit combinations – even with visual exemplars added, despite resulting in more false positives. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/041d3006-4ab9-4d5e-9ffa-c2fb0e550022
- author
- Wrisberg, Anton
LU
; Wallin, Annika
LU
and Pärnamets, Philip
- organization
- publishing date
- 2026-04-08
- type
- Working paper/Preprint
- publication status
- published
- subject
- keywords
- applied research, categorisation, conceptual spaces, exemplar theory, prototype theory, signal detection, waste sorting
- publisher
- Centre for Open Science
- DOI
- 10.31234/osf.io/5p8yt_v1
- project
- Boosting Public Waste Sorting
- language
- English
- LU publication?
- yes
- id
- 041d3006-4ab9-4d5e-9ffa-c2fb0e550022
- date added to LUP
- 2026-05-06 11:46:58
- date last changed
- 2026-05-28 09:32:41
@misc{041d3006-4ab9-4d5e-9ffa-c2fb0e550022,
abstract = {{Waste sorting signs present an inviting avenue for comparison of categorisation theories as they often contain both a rule and either an abstract prototype or visual exemplars. Focus in waste sorting studies is often on increasing the number of waste fractions, but some public settings might require fewer-than-ordinary fractions. This paper investigates two approaches to reducing a waste sorting system’s granularity at a music festival: explicit combining waste fractions by merging waste signs and implicitly combining fractions by removing alternatives to ‘residual waste’. The digital sorting results are modelled as a probit regression allowing direct interpretation in terms of signal detection theory’s senstitivy and criterion parameters. The paper further compares four alternative waste sorting signs including visual exemplars to improve waste sorting accuracy for the implicitly combined waste fraction. The results suggest that explicitly combining waste fractions outperform implicit combinations – even with visual exemplars added, despite resulting in more false positives.}},
author = {{Wrisberg, Anton and Wallin, Annika and Pärnamets, Philip}},
keywords = {{applied research; categorisation; conceptual spaces; exemplar theory; prototype theory; signal detection; waste sorting}},
language = {{eng}},
month = {{04}},
note = {{Preprint}},
publisher = {{Centre for Open Science}},
title = {{Collapsing Waste Fractions Without Reducing Sorting Accuracy}},
url = {{http://dx.doi.org/10.31234/osf.io/5p8yt_v1}},
doi = {{10.31234/osf.io/5p8yt_v1}},
year = {{2026}},
}