Evidence map›Paper›PMID 42677071›Full record

ArticleNew media & society2026

Training the algorithm: Agency and algorithmic injustice in Instagram's 'whitewashed' health and fitness spaces.

Hester Hockin-Boyers, Patricia Vertinsky, Moss Norman, Nikolaus A Dean, Aishwarya Ramachandran

Abstract read
In one paragraph

Article in New media & society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Hester Hockin-BoyersDurham University, UK.ORCID https://orcid.org/0000-0002-6675-3430
Patricia VertinskyThe University of British Columbia, Canada.
Moss NormanThe University of British Columbia, Canada.
Nikolaus A DeanUniversity of Waikato, New Zealand.ORCID https://orcid.org/0000-0003-1756-0381
Aishwarya RamachandranThe University of British Columbia, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Research on women's body image has often focused on the potential harms associated with engaging with health and fitness content on Instagram. Recently, scholars have turned their attention to exploring women's agency in relation to social media to examine how particular groups of individuals participate in the curation of their online worlds in pursuit of a positive body image. In particular, we consider the experiences of specific racial groups who are interacting with what some claim are 'whitewashed' and algorithmically biased digital environments. We aim to contribute to this enquiry by drawing on semi-structured interviews and 'content elicitation' with 32 Chinese Canadian women who were invited to describe their experiences with health and fitness content on Instagram. We found that our participants displayed a heightened awareness of algorithmic bias and in response, attempted to actively 'train' their algorithms to provide content that reflected greater bodily diversity.

Indexed as

Agencyalgorithmsbody imagecontent elicitationfitness cultureInstagramracesocial media

Identifiers

PMID42677071
PMCPMC13529204

What OpenQuestion holds

Textmetadata
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.