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Record W4296593165 · doi:10.1177/00218863221113316

Partnering for Impact: A Grand Challenge and Design for Co-Creating a Just, Resilient and Flourishing Society

2022· article· en· W4296593165 on OpenAlex

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

VenueThe Journal of Applied Behavioral Science · 2022
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsWestern University
Fundersnot available
KeywordsFlourishingEmbeddednessReflexivityPerspective (graphical)Action (physics)SociologyEpistemologyKnowledge managementEngineering ethicsPsychologySocial scienceSocial psychologyComputer scienceEngineering

Abstract

fetched live from OpenAlex

In this paper I elaborate on the design and dimensions of interorganisational collaborations particularly when the purpose of connecting is the co-creation of knowledge for impact. I extend recent accounts of co-creating knowledge and explain why co-creation is integral to the “common good” logic especially when the focus of partnering for impact embraces the marked improvements in action that constitutes the impact of collaboration. I then elaborate on “partnering for impact” as a collaborative design and explicate the axiology that this mode of co-creation calls for, marked by a fresh perspective on inclusiveness founded on isotimia and philotimia . I illustrate the manifestation of these dimensions in the GNOSIS approach of co-creating impact through the embeddedness of “re-search” as a common practice. I conclude by inviting greater reflexivity in the relationship between science and society when partnering for impact is intended to co-create a just, resilient and flourishing society.

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)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.368
GPT teacher head0.505
Teacher spread0.137 · 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