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Record W119338607 · doi:10.18584/iipj.2013.4.2.1

Evaluation of Aboriginal Programs: What Place is Given to Participation and Cultural Sensitivity?

2013· article· en· W119338607 on OpenAlexafffundvenueabout
Steve Jacob, Geoffroy Desautels

Bibliographic record

VenueInternational Indigenous Policy Journal · 2013
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsUniversité Laval
FundersSocial Sciences and Humanities Research Council of CanadaAboriginal Affairs and Northern Development CanadaIndigenous and Northern Affairs Canada
KeywordsTechnocracyCultural sensitivityCitizen journalismAutonomyParticipatory evaluationIndigenousCommissionQuality (philosophy)SociologyPolitical sciencePublic administrationPsychologyEpistemologyPoliticsLaw

Abstract

fetched live from OpenAlex

Aboriginal populations in Northern Canada have, for many years, been confronted with socio-economic problems affecting their development. In the early 1990s, the Royal Commission on Aboriginal Peoples (1996) report concluded that it was important to integrate Aboriginal people into the management of public policies that concern them and to encourage their autonomy. In order to produce a quality evaluation that is useful in particular cultural contexts, measures have been developed to assure that the evaluation highly regards cultural sensitivity while integrating local participants in the evaluation process. This study, based on the systematic analysis of a non-probability sample of 27 program evaluation reports, presents an inventory of evaluation practice in Aboriginal contexts and estimates in what measure a culturally sensitive and participatory approach was applied. It was apparent that cultural sensitivity is gradually being integrated into Aboriginal program evaluation and that certain indicators show that there has been a positive evolution in this direction. Finally, the study shows an occasional recourse to participatory approaches, but this is not a strong tendency as systematically technocratic approaches are more broadly employed.

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 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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.911
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.191
GPT teacher head0.550
Teacher spread0.359 · 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 teacher head, not a consensus.

Study designOther design
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

Citations16
Published2013
Admission routes4
Has abstractyes

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