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Record W3033375676 · doi:10.1017/s0714980820000197

Aggression and Older Adults: News Media Coverage across Care Settings and Relationships

2020· article· en· W3033375676 on OpenAlexaffabout
Laura Funk, Rachel Herron, Dale Spencer, Starr Lee Thomas

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicElder Abuse and Neglect
Canadian institutionsCarleton UniversityBrandon UniversityUniversity of Manitoba
Fundersnot available
KeywordsAggressionMainstreamAmbiguityNews mediaPsychologyMedia coverageSocial psychologyCriminologySociologyPolitical scienceMedia studiesComputer science

Abstract

fetched live from OpenAlex

Systematic, in-depth exploration of news media coverage of aggression and older adults remains sparse, with little attention to how and why particular frames manifest in coverage across differing settings and relationships. Frame analysis was used to analyze 141 English-language Canadian news media articles published between 2008 and 2019. Existing coverage tended towards stigmatizing, fear-inducing, and biomedical framings of aggression, yet also reflected and reinforced ambiguity, most notably around key differences between settings and relations of care. Mainstream news coverage reflects tensions in public understandings of aggression and older adults (e.g., as a medical or criminal issue), reinforced in particular ways because of the nature of news reporting. More nuanced coverage would advance understanding of differences among settings, relationships, and types of actions, and of the need for multifaceted prevention and policy responses based on these differences.

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)0.005
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.398
Threshold uncertainty score0.802

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0160.018
Science and technology studies0.0020.001
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.241
Teacher spread0.227 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations16
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal on Aging / La Revue canadienne du vieillissementSame topicElder Abuse and NeglectFrench-language works237,207