Evidence map›Paper›PMID 35257092›Full record

ArticleForensic science international. Synergy2022

The strange persistence of (source) "identification" claims in forensic literature through descriptivism, diagnosticism and machinism.

Alex Biedermann

Erratum issuedAbstract read
In one paragraph

Article in Forensic science international. Synergy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Stylometry and forensic science: A literature review.Forensic science international. Synergy · 2024
    Review
  7. The scientific reinvention of forensic science.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  8. Review
  9. Review
  10. Article
  11. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author.

Alex BiedermannUniversity of Lausanne, School of Criminal Justice, 1015 Lausanne-Dorigny, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many forensic scientists consider that identification (individualisation) - in the sense of statements of the kind "the questioned item and the known item come from the same source" - is a concept that is central to their discipline. This is so despite decade-long, fundamental critiques levelled by both practitioners and academics against the conceptual and practical feasibility of forensic identification. Oddly, there is a constant stream of publications in (peer-reviewed) forensic science journals that treat forensic identification axiomatically as a valid object of study, sidestepping the fundamental critiques. This paper reviews and discusses three exemplary strands of publications that exemplify this persistent trend. These strands are called descriptivism, diagnosticism and machinism. The latter term refers to methods borrowed from the now increasingly popular approaches used in the field of machine learning. In turn, descriptivism and diagnosticism refer to general design aspects of mainstream research methods, illustrated here through a critical review of two recent papers on, respectively, forensic odontology and a framework for interpreting fingerprint evidence. The critique of the use of 'identification' in these strands of publication includes, but goes beyond, semantic details and the reiteration of long-known shortcomings of obsolete technical language such as 'match' and 'matching'. Specifically, this paper exposes deeper problems such as the subtle and argumentatively unfounded carrying-over of source conclusions to ultimate issues and the use probability concepts for questions that require more than the mere quantification of uncertainty. This paper submits that in order to foster trust in an era of continually expanding publishing activities, it should be a vital interest to forensic science journals to better examine what identification-related research can and cannot legitimately purport to achieve.

Indexed as

Artificial intelligenceDescriptive researchDiagnostic reasoningIdentification/individualisationMachine learning

Identifiers

PMID35257092
PMCPMC8897692

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.