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Record W3049501884 · doi:10.1177/2096531120932579

Beyond Well-being: The Quest for Wholeness and Purpose in Education

2020· article· en· W3049501884 on OpenAlexaboutno aff
Dennis Shirley

Bibliographic record

VenueECNU Review of Education · 2020
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsnot available
Fundersnot available
KeywordsInclusion (mineral)Value (mathematics)EpistemologySociologyOriginalityWell-beingField (mathematics)Set (abstract data type)Engineering ethicsCapability approachEnvironmental ethicsPolitical scienceSocial scienceQualitative researchPhilosophyLaw

Abstract

fetched live from OpenAlex

Purpose: This article develops a critique of contemporary understandings and practices related to well-being in education. It proposes a fuller development of wholeness and purpose that supplements and goes beyond the new well-being agenda. Design/Approach/Methods: This article draws upon a document analysis of conceptual and policy frameworks related to well-being. It builds its critique of well-being with reference to a qualitative study consisting of 222 interviews with educators in the Canadian province of Ontario with regard to their understandings of well-being. It includes references to the research and development work in the U.S., Germany, and Norway. Findings: The inclusion of well-being in policy agendas is an important step forward in the field of educational change, but this indication of progress is in danger of being reified through simplistic understandings of life satisfaction and other frameworks that evade the complexity of human development. Wholeness and purpose are concepts that include but also go beyond well-being that should be addressed by educators. Originality/Value: Most of the criticisms of the new well-being agenda in educational policies and research simply assume its status as a summum bonum for human development. This essay acknowledges the importance of well-being but expands beyond it to define wholeness and purpose as an alternative set of constructs with their own independent integrity that should not simply be subsumed into current well-being agendas.

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)0.016
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0060.097
Scholarly communication0.0140.018
Open science0.0020.008
Research integrity0.0030.009
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.363
Teacher spread0.342 · 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 designTheoretical or conceptual
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

Citations20
Published2020
Admission routes1
Has abstractyes

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