Supporting Experiment — Emily Rivera Interview

Following the toolkit naming conventions, this file is named exp-04.b-conversation-emily-rivera-2025-02-25.qmd.

General Info

  • Title / Observation Type: Interview with Emily Rivera, Professional Woman Commuter
  • Date: 2025-02-24
  • Location / Setting: Downtown Manhattan → Brooklyn (late evening return, ~9:30 PM)
  • Team Member(s): Nile
  • Modality: Interview (exploratory)
  • Linked Primary Experiment: Diamond 2 — Pain Discovery & Validation for Professional Women Commuters

1. Clarify the Unknown

  • Most Urgent Unknown: When and why do professional women feel least secure during commutes, and how do they manage that risk?
  • Other Urgent Unknowns: How do time-of-day, lighting, and crowd density interact with perceived safety? What self-protective routines emerge (if any)?

2. Experiment Type

3. Modality and Fit

  • Modality Chosen: Guided conversation using the Halo Alert Conversation Guide (story-first; emotional probes).
  • Why it fits: Captures lived experiences across commute segments (street → platform → train → egress) and surfaces emotional triggers (lighting, sparsity, proximity).

4. Design

  • Source of Evidence: Professional women commuters near subway entrances/exits.
  • Collection Mechanism: Walk-up interview; recorded with consent using the Conversation Guide.
  • Sampling Strategy: Convenience sample at evening end-of-day; bias toward office workers leaving late.
  • Sample Size Goal: 2–5 initial interviews in this time window (Emily = evening/late case).

5. Execution Notes

  • Approached outside a downtown Manhattan station as Emily left work later than usual.
  • Interview covered full journey home (downtown → Brooklyn) with emphasis on late hour and lighting conditions.
  • Duration: ~20 minutes; recorded with consent.
  • Deviations: Probed more on route changes and lighting after she mentioned a prior mugging incident nearby (not personally experienced).
  • Sampling bias: Skews toward late-evening commuter experience; not generalizable to daytime riders without additional interviews.

6. Results and Data Summary

Representative Evidence (Excerpts): - Late-night context & vigilance:
“My commute home was much later than usual, around 9:30 PM… fewer people, dimmer street lights… I kept my headphones off to be fully aware.”

  • Train sparsity = eerie:
    “The subway car was less crowded… nice to have more space, but the sparsity can feel eerie. I kept my bag close and avoided eye contact.”

  • Last-leg walk & micro-tactics:
    “The streets were almost empty… every sound seemed amplified… I walked briskly, keys in my hand, stayed in well-lit areas.”

  • Underlying concerns vs. daytime:
    “I generally feel secure during regular hours… after dark I’m more aware of my surroundings and who’s around me.”

  • Route change after incident nearby:
    “I stopped taking a shortcut through a poorly lit alley after hearing about a mugging there… Now I take a longer, better-lit route with more people.”

  • Safety through connection:
    “I’ll text my sister or a close friend, share my location or check in… If they don’t hear from me by a certain time, they know to reach out.”

Themes Identified: - Lighting & Timing: Darkness elevates vigilance; lighting quality is a major moderator of perceived safety.
- Density Curve: Both high density (crowded) and low density (sparse) carry different discomforts; late-night sparsity triggers eeriness.
- Micro-Tactics for Control: Keys in hand, headphones off, route selection to maximize light/visibility/foot traffic.
- Safety Through Connection: Proactive messaging + ETA accountability with loved ones.
- Convenience vs. Safety Trade-off: Willing to pay “time cost” (longer route) to reduce perceived risk.

Raw Materials & Links: - Full transcript: Exp 04.b — Commuter Conversation: Emily Rivera

7. Knowledge Updating

  • What do we now know?
    Late-evening conditions (low density + low light) shift commuters’ strategies toward situational awareness and connection-based reassurance. perceived safety is strongly tied to environmental controllability (light, sight lines, proximity of others).
  • Confidence: Moderate — converges with Sarah’s patterns (connection routines), but adds strong lighting/timing dimension; needs more off-peak interviews.
  • Assumptions Updated/Abandoned:
    • Updated: “Physical risk” proxies (e.g., reported incidents) influence route choice even when not personally experienced.
    • Abandoned: Assumption that crowding alone is the main driver; sparsity can be equally unsettling for different reasons.

8. Next Steps

  • Broaden sampling: Add commuters on bus, rideshare, and bike; include early-morning riders and weekend late nights for contrast.
  • Observation pairing: Evening station/egress observations to validate lighting, foot traffic, and behavior cues.
  • Hypothesis shaping: Draft pain hypothesis around “reassurance under low-control conditions” (low light, low density, unfamiliar routes).
  • Design signal tests: Explore low-friction check-in mechanisms and discreet triggers that work with hands full or phone stowed.