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Record W1974137863 · doi:10.1177/0092055x15569316

The Game of Social Life

2015· article· en· W1974137863 on OpenAlexaffabout
Kosha D. Bramesfeld, Arla Good

Bibliographic record

VenueTeaching Sociology · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Teaching Methodologies in Social Sciences
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsPrivilege (computing)SociologyPovertyAgency (philosophy)Social inequalityOppressionSocial psychologyInequalitySocial stratificationPerspective (graphical)PsychologyPedagogySocial scienceEconomic growthPoliticsPolitical science

Abstract

fetched live from OpenAlex

This article presents the development of a new simulation activity, the Game of Social Life. The activity introduces students to concepts of social stratification based on multiple dimensions of poverty, including inequalities related to housing, education, occupational status, social power, and health outcomes. The game was administered to students enrolled in a social psychology course at a small, private, liberal arts university located in the midwestern United States. Qualitative analysis of 25 students’ written reactions revealed that the game was engaging and successful in motivating students to adopt a new perspective, acknowledge inequality and explanations for poverty, self-reflect about privilege and oppression, and consider solutions to these problems. The activity was also assessed as a training exercise with 16 staff members at a nonprofit agency located in an urban area in southeastern Canada. These assessments indicate that the activity can be used in a variety of contexts.

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)0.002
metaresearch head score (Gemma)0.006
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: Methods · Consensus signal: Methods
Teacher disagreement score0.014
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.003
Scholarly communication0.0030.003
Open science0.0020.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.002

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 head0.250
GPT teacher head0.481
Teacher spread0.231 · 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
GenreMethods

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

Citations18
Published2015
Admission routes2
Has abstractyes

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