“Bring in your parents day”: building inclusion and engagement through a cross-generational family-friendly workplace initiative
Bibliographic record
Abstract
Purpose Employer-sponsored family-friendly events are designed to boost engagement and encourage retention by building family members’ identification with the organization. These events are usually targeted at employees with dependent children, but LinkedIn’s more inclusive “Bring in Your Parents” (BIYP) initiative aims to introduce employees’ parents to the daily work of their adult children. This study evaluates the impact of BIYP on the attitudes and behavioral intentions of participating employees and their parents. Design/methodology/approach Repeated-measures surveys were conducted among participating employees and parents in six organizations in six countries (UK, Ireland, France, Brazil, Mexico and Colombia). These were followed by in-person interviews with participating employees (UK) and phone interviews with HR managers (Brazil, Canada, France, Spain, UK and USA). Findings Participation in BIYP increases employee engagement and parents’ instrumental and affective support for their children and for their children’s employers. Hosting BIYP is perceived to enhance corporate reputation among both internal and external stakeholders. Practical implications BIYP serves the dual function of building employee engagement and creating new parental brand ambassadors for participating organizations. BIYP can be an effective tool for employers to engage members of staff not traditionally included in organizational family-friendly events and may be particularly useful for firms with a high proportion of younger workers in tech-savvy jobs. Originality/value This evaluation of a new workplace initiative demonstrates measurable effects on important employee attitudes and behavioral intentions.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 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".