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Record W3084323283 · doi:10.1111/ijsw.12442

Managing the tensions between service and advocacy: The case of the AJEEC Social Change Service Organization, Naqab, Israel

2020· article· en· W3084323283 on OpenAlexaff
Amal Elsana

Bibliographic record

VenueInternational Journal of Social Welfare · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Society, and Development
Canadian institutionsMcGill University
Fundersnot available
KeywordsDilemmaPublic relationsEmpowermentSocial workSustainabilityPoliticsService (business)Social changeSociologyCivil societyPublic administrationPolitical scienceIndigenousPower (physics)BusinessLawMarketing

Abstract

fetched live from OpenAlex

The tension between providing services to marginalized groups and organizing them for advocacy to challenge power structures is a fundamental dilemma for Social Change Service Organizations (SCSO). This dilemma exists in many civil society organizations, especially those that work with indigenous communities, such as the Bedouin in Israel, where providing immediate services and advocating for policy change are crucial. Literature shows the tensions that arise from combining service provision and advocacy. However, there are very few studies showing how these organizations manage and overcome these tensions sustainably. The present study is an exploratory case study using the AJEEC (Arab‐Jewish Center for Empowerment, Equality, and Cooperation) in the Naqab as an instrumental single case. It provides an in‐depth understanding of the tensions AJEEC is facing and reveals AJEEC’s unique approach and strategies for managing these tensions effectively and sustainably within the social, political, and cultural contexts. It presents implications for research, policy, and practice.

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)0.007
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0450.018
Scholarly communication0.0110.004
Open science0.0030.009
Research integrity0.0090.008
Insufficient payload (model declined to judge)0.0050.001

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 head0.041
GPT teacher head0.309
Teacher spread0.268 · 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

Citations7
Published2020
Admission routes1
Has abstractyes

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