Reconsidering Maslow and the hierarchy of needs from a First Nations’ perspective
Bibliographic record
Abstract
INTRODUCTION: Abraham Maslow created one of the most enduring psychological constructs, the hierarchy of needs. Maslow, himself, did not create the oft-shown pyramid but it is the image that comes to mind when the construct is mentioned. There have also been reports that Maslow’s work fails to give due credit to the Blackfoot peoples of Southern Alberta for their seminal contribution to the hierarchy. There is a vibrant debate in the literature and in public spaces regarding this. Such a debate may not matter as Maslow’s construct does not represent Blackfoot philosophy. Hierarchical needs of understanding are not representative of their world view and the place of self-actualisation is very contrary to Maslow’s understanding. Maslow’s own writings do not support the notion that Blackfoot knowledge influenced him greatly in respect of the construct. In concert with the Elder knowledge keeper in the project, we explore the history of Maslow and the Blackfoot people along with knowledge held by Elder wisdom. APPROACH: The article concludes by suggesting that Blackfoot ways of knowing represent their own views and that Maslow’s hierarchy has never been their understanding. IMPLICATIONS: Social workers are, thus, invited to critically assess the theories used in practice and their relevance and validity for the populations engaged in their work.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.012 | 0.043 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.007 |
| 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".