Quantitative Breakdown of Credit Patterns
In volunteer communities, credit is not vanity — it's infrastructure. When people's work is acknowledged, they feel valued and continue contributing. When credit is taken or erased, contributors become invisible and eventually leave.
This page provides quantitative analysis of Elle's credit patterns compared to other contributors, based on Discord message analysis.
Analysis of Discord messages (Noisebridge server, July 2024 - December 2025) tracking:
| Metric | Elle | Elan | LX | j.d. | zoda |
|---|---|---|---|---|---|
| Total Messages | 2,276 | 5,195 | 1,526 | 2,356 | 1,274 |
| Credits Given | 8 | 11 | 2 | 12 | 5 |
| Self-Credits | 24 | 21 | 6 | 9 | 5 |
| Credit Ratio | 0.33 | 0.52 | 0.33 | 1.33 | 1.00 |
| Self-Credit Rate | 1.05% | 0.40% | 0.39% | 0.38% | 0.39% |
Elle made 252 announcements using "we got/have/did" language. None explicitly credited the people who actually did the work.
"We got a grant!"
Who wrote the grant? Unknown.
"We have 2 new machines coming in!"
Who acquired them? Who transported them? Who set them up? Unknown.
"Membership drive going strong!"
Who organized it? Who's running it? Unknown.
When someone says "We did X" without naming names, listeners make an association. The announcer becomes implicitly credited. Over 252 announcements:
Explicit self-credit: messages containing "I did", "I made", "I organized", etc.
| Person | Self-credits | Total messages | Rate |
|---|---|---|---|
| Elle | 24 | 2,276 | 1.05% |
| Elan | 21 | 5,195 | 0.40% |
| LX | 6 | 1,526 | 0.39% |
| j.d. | 9 | 2,356 | 0.38% |
| zoda | 5 | 1,274 | 0.39% |
All five contributors did real work. The difference is in how they talked about it:
| Elle's Pattern | Others' Pattern |
|---|---|
| "I organized the fashion show" | "Thanks to @A, @B, and @C for making the event happen" (zoda) |
| "I ran the sewing class" | "Huge kudos/shoutout to @X for debugging the Wiki!" (Elan) |
| "I helped with the grant" | "Big thanks to @A and @B for scanning" (LX) |
| "We got new machines" (no attribution) | "Thank you @Y, that was a fun and informative class" (j.d.) |
Credit ratio: (credits given ÷ self-credits). Ratio above 1.0 means giving more credit than taking. Below 1.0 means taking more than giving.
| Person | Messages | Credits Given | Self-Credits | Ratio |
|---|---|---|---|---|
| Elle | 2,276 | 8 | 24 | 0.33 |
| Elan | 5,195 | 11 | 21 | 0.52 |
| LX | 1,526 | 2 | 6 | 0.33 |
| j.d. | 2,356 | 12 | 9 | 1.33 |
| zoda | 1,274 | 5 | 5 | 1.00 |
Critical Difference: Despite similar message volume to j.d. (2,276 vs 2,356), Elle gave credit only 8 times vs j.d.'s 12, while taking credit 24 times vs j.d.'s 9.
Analysis of questions in #sewing shows how credit-taking and bottlenecking reinforce each other:
"Please advise from Elle over me"— Jet
"Elle would know"— Mike
"@Elle do you know..."— Pattern repeated dozens of times
See: Bottleneck Pattern for full analysis
When Elle says "we got new machines" without naming who acquired them, those people's work becomes invisible. After enough repetitions, they stop volunteering.
Potential helpers see that Elle does everything and gets associated with everything. They assume there's no room for them, or that their work won't be recognized.
Elle complained "no one comes to my meetings." But when credit flows one direction, why would people attend meetings where they won't be acknowledged?
The credit imbalance creates interpersonal friction that makes the space feel less welcoming.
j.d., zoda, and Elan consistently credited others by name. Here are real examples:
| Type | j.d. | zoda | Elan |
|---|---|---|---|
| Announcements | "Thank you @X, that was a fun and informative class!" | "Thanks to @A, @B, and @C for making the event happen" | "Huge kudos/shoutout to @X for debugging the Wiki!" |
| Accomplishments | "Thank you @Y for the photo and the tip" | "@A did the hard work" | "Shoutout to @Z for the speedy diagnosis!" |
| Collaborative Work | "Thank you @A for helping calm the situation" | "Great session with @B learning about Y" | "Thank you @C! Definitely a critical part of the path" |
| Credit Ratio | 1.33 (gives 33% more) | 1.00 (balanced) | 0.52 (deficit but better per-message rate) |
| Pattern | How Credit-Taking Enables It |
|---|---|
| Bottleneck Pattern | When credit flows to one person, questions route to them, reinforcing centralization |
| Policy Injection | Being seen as "the expert" (via credit accumulation) makes fabricated rules more believable |
| Escalation Moves | Accumulated credit creates perceived authority to make demands |
| Mediator Burnout | Pattern of not acknowledging others' contributions extends to mediation, burning out facilitators |
| Red Flag | What It Looks Like |
|---|---|
| Frequent "we did" with no names | Announcements that create associations without attribution |
| People stop volunteering | Initial enthusiasm that fades when work isn't acknowledged |
| All questions route to you | "Ask @You" becomes the default answer |
| "No one helps anymore" | Complaint that others stopped contributing |
| You're seen as "doing everything" | Community views you as sole contributor despite others' work |
252 unattributed announcements erased contributors and reinforced bottleneck
Announcements without names create implicit associations with the announcer
Elle's 1.05% vs Elan (0.40%), LX (0.39%), j.d. (0.38%), zoda (0.39%) — consistent pattern across multiple comparisons
Elle's 0.33 ratio (takes 3x more than gives) vs j.d.'s 1.33 (gives 33% more than takes) and zoda's 1.00 (balanced)
Elle (2,276 messages) vs j.d. (2,356 messages): Elle gave credit 8 times vs j.d.'s 12, took credit 24 times vs j.d.'s 9
Low meeting attendance, no new volunteers, gaps when Elle left
Enables bottleneck, supports policy injection authority, creates interpersonal friction