Kindness-informed allyship praxis
Bibliographic record
Abstract
Purpose This paper explores intergenerational perceptions of kindness in the context of Black Lives Matter (BLM) movement and the COVID-19 global pandemic. The purpose of this exploratory study is to investigate perceptions of kindness in the context of traumatic events and its potential value in authentic allyship in organizational environments. Design/methodology/approach Authors interviewed 65 individuals (31 self-identifying as non-racialized and 34 self-identifying as Black, Indigenous and People of Colour aka BIPOC). Participants included Generation Z (Gen Z; born between 1997–2012/5) and Generation Y (Gen Y; also referred to as Millennials, born between 1981 and 1994/6) across North American, Europe and Africa. Millennials currently represent the largest generation in the workplace and are taking on leadership roles, whereas Gen Z are emerging entrants into the workplace and new organizational actors. Findings The paper offers insights into how to talk about BLM in organizations, how to engage in authentic vs performative allyship and how to support BIPOC in the workplace. The study also reveals the durability of systemic racism in generations that may be otherwise considered more enlightened and progressive. Research limitations/implications The authors expand on kindness literature and contribute theoretically and methodologically to critical race theory and intertextual analysis in race scholarship. Practical implications The study contributes to the understanding of how pro-social behaviours like kindness (with intention) can contribute to a more inclusive discourse on racism and authentic allyship. Originality/value Authors reveal the potential for kindness as a pro-social behaviour in organizational environments to inform authentic allyship praxis.
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 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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.016 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".