Evidence map›Paper›PMID 32683609›Full record

ArticleMedicine, health care, and philosophy2020

Fair trade in building digital knowledge repositories: the knowledge economy as if researchers mattered.

Giovanni De Grandis

Abstract read
In one paragraph

Article in Medicine, health care, and philosophy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Knowledge repositories. In digital knowledge we trust.Medicine, health care, and philosophy · 2020
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Giovanni De GrandisDepartment of Philosophy and Religious Studies, Norwegian University of Science and Technology (NTNU), NTNU Dragvoll, 7491, Trondheim, Norway. giovanni.grandis@ntnu.no.ORCID http://orcid.org/0000-0002-1948-7467

Funding

Wellcome TrustWellcome Trust 201576/Z/16/Z
6 · The paper itself

Abstract

Both a significant body of literature and the case study presented here show that digital knowledge repositories struggle to attract the needed level of data and knowledge contribution that they need to be successful. This happens also to high profile and prestigious initiatives. The paper argues that the reluctance of researchers to contribute can only be understood in light of the highly competitive context in which research careers need to be built nowadays and how this affects researchers' quality of life. Competition and managerialism limit the discretion of researchers in sharing their results and in donating their working time. A growing corpus of research shows that academic researchers are increasingly overworked and highly stressed. This corroborates the point that the room for undertaking additional tasks with future and uncertain benefits is very limited. The paper thus recommends that promoters of digital knowledge repositories focus on the needs of the researchers who are expected to contribute their knowledge. In order to treat them fairly and to ensure the success of the repositories, knowledge sharing needs to be rewarded so as to improve the working conditions of contributors. In order to help implementing this researcher-centred approach, the paper proposes the idea of expediential trust: rewards for contributing should be such that rational, self-interested researchers would freely decide to contribute their knowledge and effort trusting that this would make them better off.

Indexed as

TrustBiomedical ResearchHumansInformation DisseminationInformation Storage and RetrievalKnowledgeResearch PersonnelCompetition in researchData sharingExpediential trustIncentives and rewardsKnowledge repositories

Identifiers

PMID32683609
PMCPMC7538398

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.