MétaCan
Menu
Back to cohort
Record W4381046522 · doi:10.15173/sciential.v1i10.3345

Social Justice Movements: Fighting for a better tomorrow

2023· article· en· W4381046522 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueSciential - McMaster Undergraduate Science Journal · 2023
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsMcMaster University
Fundersnot available
KeywordsInfographicGlobeEquity (law)Public relationsEconomic JusticeSocial justicePolitical scienceSocial movementSpace (punctuation)SociologyPsychologyCriminologyComputer scienceLawPolitics

Abstract

fetched live from OpenAlex

Social justice movements are an essential factor in driving change and ensuring equity for everyone. Globally, there are several issues prevailing that do not receive adequate attention, which causes victims to suffer. Social justice implies the idea that everyone deserves equal rights and access to good health. Unified societal efforts have the potential to tackle large-scale problems across the globe. This infographic aims to raise awareness regarding some of the issues the world is facing and presents society-driven movements as a way of calling attention to the problems and finding pathways to solutions. Examples of successful movements are mentioned in this infographic, and statistics shown prove that collective efforts are needed to ensure a safe space for everyone. This infographic also provides vital information regarding the funds raised for three movements and the number of individuals taking part in fighting for the cause.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.260
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0180.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.187
GPT teacher head0.476
Teacher spread0.289 · 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