Inclusion Needs Through the Lens of Intersectionality: Evidence supporting The 8-Inclusion Needs of All People Framework
Bibliographic record
Abstract
This paper makes a substantial contribution to the fields of inclusion and intersectionality. It addresses the recognized gap in applying intersectionality as a practical framework for creating inclusive environments for all identities and intersectionalities. Drawing upon existing consensus among researchers on the importance of intersectionality, the study conducted in 2023 employs a robust qualitative methodology involving narrative interviews with 22 participants living in the United States, Canada, Australia, and the United Kingdom and representing diverse identities and intersectionalities to understand their identities, lived-experience and inclusion needs to thrive in work and life. Thematic analysis of participant responses resulted in support of all inclusion needs proposed in Wilson’s (2023) 8-Inclusion Needs of All People framework; Access, Space, Opportunity, Allowance, Representation, Language, Respect, and Support. Consequently, this research paper provides empirical evidence on the applicability of the 8-Inclusion Needs of All People framework, as proposed by Wilson (2023), in addressing multifaceted inclusion needs through the lens of intersectionality to prevent discrimination and promote equity and equal outcomes for all people. Further, as underscored by the participant's insights, it is essential to pivot from conventional approaches that endeavour to assimilate individual identities into pre-existing structures towards a more progressive stance that actively create inclusive organizations to embrace the diverse tapestry and inclusion needs of all people and their intersectionalities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".