MétaCan
Menu
Back to cohort
Record W2941588150 · doi:10.31234/osf.io/9agdp

Dialecticism across the Lifespan: Towards a Deeper Understanding of the Ontogenetic and Cultural Factors Influencing Dialectical Thinking and Emotional Experience

2017· preprint· en· W2941588150 on OpenAlexaff
Igor Grossmann

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsDialecticConstruct (python library)Cultural psychologyPsychologyContext (archaeology)EpistemologyMaturity (psychological)Empirical evidenceEmpirical researchSociologyCognitive scienceDevelopmental psychologyHistory

Abstract

fetched live from OpenAlex

Before dialecticism became a topic of empirical inquiry in cultural psychology, scholars in related disciplines has discussed dialecticism as a model of human development, as an essential component of maturity and wisdom. This review chapter bridged these two perspectives, comparing conceptualizations of dialecticism in developmental and cultural psychology. After reviewing historical portrayals of dialecticism in various philosophical traditions, this chapter provides comparison of historical characterizations with the contemporary treatment of dialecticism in human development and cultural psychology. Both streams -- developmental and cross-cultural -- are proposed as essential for an integral understanding of the construct. Subsequently, the chapter discusses the emerging developmental models of dialecticism across the lifespan and reviews the accompanying empirical evidence, situating it in a cross-cultural context. It concludes with an outline of future directions of research on dialectical thought, with attention to psychological and socio-cultural processes engendering dialecticism across the lifespan.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.480
Threshold uncertainty score0.876

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.228
GPT teacher head0.421
Teacher spread0.193 · 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 teacher head, 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

Citations2
Published2017
Admission routes1
Has abstractyes

Explore more

Same topicCultural Differences and ValuesFrench-language works237,207