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Record W2152737464 · doi:10.1177/0021886313518965

How Dr. Akhtar Hameed Khan Led a Change Process That Started a Movement

2014· article· en· W2152737464 on OpenAlexaffabout
Richard E. Boyatzis, Masud Khawaja

Bibliographic record

VenueThe Journal of Applied Behavioral Science · 2014
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsEmpowermentIntervention (counseling)SociologyPublic relationsHonorCommunity developmentSocial changeCommunity organizationProcess (computing)Quarter (Canadian coin)Political scienceManagementEconomic growthPsychology

Abstract

fetched live from OpenAlex

In 1956, Akhtar Khan began a project in rural East Pakistan that inspired new approaches to community and organization development. A quarter century later, he replicated the developmental process in impoverished neighborhoods of Karachi. The techniques of shared decision making, building cooperatives, training the master trainers, and encouraging self-sufficiency were pivotal to the approach. The effect transformed the two communities and helped inspire microfinance. Using the lens of intentional change theory in a post hoc analysis, we explain why this approach worked. The article allows us to honor a social innovator while affirming our commitment to practices like participation to create and reinforce a shared vision, creating new resonant relationships, building a multilevel intervention with distributed leadership, inclusiveness in training for empowerment, and continuous attention to cycling through the process iteratively. These are offered as insights in the design of organization and community development efforts.

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)0.007
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.019
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0120.008
Scholarly communication0.0080.007
Open science0.0010.005
Research integrity0.0040.011
Insufficient payload (model declined to judge)0.0090.003

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 head0.195
GPT teacher head0.452
Teacher spread0.257 · 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 designQualitative
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

Citations6
Published2014
Admission routes2
Has abstractyes

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