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Incorporating Immigrant Perspectives Into Organizational Research and Practice: Implementing Inclusive Discussions

2015· article· en· W1991274604 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

VenuePracticing Anthropology · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicAnthropology: Ethics, History, Culture
Canadian institutionsTrinity CollegeWilfrid Laurier University
Fundersnot available
KeywordsParticipatory action researchNegotiationPublic relationsCitizen journalismSociologyInclusion (mineral)Political scienceBusinessSocial scienceLaw

Abstract

fetched live from OpenAlex

Anthropologists have "been in business" with for-profit and not-for-profit organizations (NPOs) for most of the 20th century, and their role as consultants for such corporations, research firms, and local organizations has continued to grow since this time (Jordan 2013). When they invest in community-based research through these partnerships, NPOs often hope to acquire meaningful and relevant evidence about practices in their communities. Yet, NPOs are unable to realize many of their potential collaborations with academics due to their dependency on elaborate and increasingly competitive funding frameworks constructed by granting bodies (INTRAC 2012). Furthermore, Morris and Luque (2011) have argued that community-based organizations and coalitions have limited input from the populations they hope to represent. Consequently, the representation and inclusion of diverse populations throughout the research process continues to be a struggle. This includes participation in data collection, project development, creation of evaluation measures, and the negotiation of program and/or policy development. Despite these limitations, participatory-action research is shown to provide long-term partnerships between both academics and their collaborators (INTRAC 2012).

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)0.010
metaresearch head score (Gemma)0.069
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.938
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.069
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0080.014
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.121
GPT teacher head0.513
Teacher spread0.393 · 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