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Record W3113850465 · doi:10.5604/01.3001.0014.6227

Hope-Action Theory and Practice

2020· article· en· W3113850465 on OpenAlexaff
Norman E. Amundson, Spencer G. Niles, Hyung Joon Yoon

Bibliographic record

VenueEducational Psychology · 2020
Typearticle
Languageen
FieldPsychology
TopicOptimism, Hope, and Well-being
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCLARITYPsychological interventionAction researchSet (abstract data type)Action (physics)PsychologyIntervention (counseling)Process (computing)Computer sciencePedagogy

Abstract

fetched live from OpenAlex

Hope-Action Theory presents a theoretical structure that holds Hope as the center point of career development. Associated with hope are competencies such as self-reflection, self-clarity, visioning, goal setting and planning, implementation, and adapting. There also are environmental factors that influence the entire career development process. In order to assess the practical utility of Hope-Action Theory a series of intervention research studies were initiated in different contexts. This article reviews the results from these studies. The first one applied specific active interventions with a group of internationally trained health professionals. The second study involved unemployed clients using a series of face-to-face and online interventions. The third group focused on the needs of refugees and was set up with a control and experimental groups using a two week group delivery approach. Positive results from all of these studies supports the utility of Hope-Action Theory and the set of active interventions that were used in this research.

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)0.017
metaresearch head score (Gemma)0.016
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 score0.017
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0040.038
Scholarly communication0.0080.006
Open science0.0020.006
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0060.001

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 head0.071
GPT teacher head0.447
Teacher spread0.376 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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