Culturally and contextually adaptive indicators of organizational success: Nunavik, Quebec
Bibliographic record
Abstract
OBJECTIVE: This study aimed to develop a preliminary guide to culturally and contextually relevant indicators to assess community resources in the 14 communities of the Inuit territory of Nunavik, Quebec. METHODS: As part of the Community Component of Qanuilirpitaa? of the 2017 Nunavik Health Survey, data were collected from 354 organizations located across Nunavik. Data were collected via short structured interviews with representatives of the organization. An inductive qualitative analysis was conducted to identify emerging themes describing the contexts that influence organizations, how key informants conceptualized what is a successful resource, and the facilitators and needs to achieving these indicators of success. Inuit partners were involved throughout the project to offer insight and to ascertain its pertinence and validity. RESULTS: Interviews revealed structural and community realities that influenced organizations. Three main indicators were used to describe successes: (1) team efficiency and dynamics; (2) accessibility of the resource; and (3) ability to impact clients and the community. The third indicator was by far the most discussed indicator of success. Participants and leaders offer suggestions as to how to achieve these indicators and advocate for the conditions necessary for organizational sustainability. CONCLUSION: This data-driven framework suggests that the measures of success that are frequently used by funding agencies (e.g., number of people reached, number of activities) may not fully represent the potential of local services in a given community. Indeed, services may be creating job opportunities for Inuit, instilling pride, offering cultural opportunities, and increasing capital (human, economic, health) within the community, all of which are equally important indicators of success that may more adequately further improve the social determinants of health among communities.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".