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Reclaiming<i>SPSSI</i>'s Sociological Past: Marie Jahoda and the Immersion Tradition in Social Psychology

2011· article· en· W1949732193 on OpenAlex
Alexandra Rutherford, Rhoda K. Unger, Frances Cherry

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.

Bibliographic record

VenueJournal of Social Issues · 2011
Typearticle
Languageen
FieldPsychology
TopicAcademic and Historical Perspectives in Psychology
Canadian institutionsCarleton UniversityYork University
Fundersnot available
KeywordsSociologySensibilityNarrativeDisciplineGender studiesSocial psychologyPsychologySocial scienceLaw

Abstract

fetched live from OpenAlex

Aspects of the life and work of Society for the Psychological Study of Social Issues (SPSSI)'s first female president, Marie Jahoda (1907–2001), are examined to help reclaim social psychology's, and SPSSI' s, lost connection to sociology. Throughout her career, Jahoda promoted a nonreductionistic, problem‐focused sociological social psychology that was profoundly influenced by her early interdisciplinary training and by subsequent collaborations with other SPSSI members in New York City in the decade following WWII. Her use of the participant observation method, or immersion approach, was an outgrowth of her sociological sensibility. She used this approach to describe and explain the complex interactions between individuals and social structures in real‐life settings. By placing Jahoda at the center of our analysis, we aim to complicate standard historical narratives about the loss of the sociological tradition within social psychology and re‐assess the relationship between the two social psychologies. We argue that her legacy should be brought to bear on contemporary debates about SPSSI's social relevance and may help re‐envision the disciplinary boundaries of contemporary social psychology.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.467
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.085
GPT teacher head0.393
Teacher spread0.308 · 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