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Record W4298003613 · doi:10.1177/14614448221122186

Difficult heritage on social network sites: An integrative review

2022· article· en· W4298003613 on OpenAlexaff
Ingrida Kelpšienė, Donata Armakauskaitė, Viktor Denisenko, Kęstas Kirtiklis, Rimvydas Laužikas, Renata Stonytė, Lina Murinienė, Costis Dallas

Bibliographic record

VenueNew Media & Society · 2022
Typearticle
Languageen
FieldPsychology
TopicMemory, Trauma, and Commemoration
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSocial mediaSituatedSociologyMedia studiesWorld Wide WebComputer science

Abstract

fetched live from OpenAlex

Social network sites (SNS) have recently become an active ground for interactions on contested and dissonant heritage, on the heritage of excluded and subaltern groups, and on the heritage of collective traumatic past events. Situated at the intersection between heritage studies, memory studies, Holocaust studies, social media studies and digital heritage studies, a growing body of scholarly literature has been emerging in the past 10 years, addressing online communication practices on SNS. This study, an integrative review of a comprehensive corpus of 80 scholarly works about difficult heritage on SNS, identifies the profile of authors contributing to this emerging area of research, the increasing frequency of publication after 2017, the prevalence of qualitative research methods, the global geographic dispersion of heritage addressed, and the emergence of common themes and concepts derived mostly from the authors ‘home’ fields of memory studies, heritage studies and (digital) media studies.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0090.012
Science and technology studies0.0010.002
Scholarly communication0.0040.005
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.063
GPT teacher head0.342
Teacher spread0.279 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations13
Published2022
Admission routes1
Has abstractyes

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