What we measure
We publish a multidimensional scorecard rather than a single mysterious number. Each dimension is scored separately, carries its own confidence value, and links to the evidence behind it.
| Dimension | What it means | Evidence |
|---|---|---|
| Role Competency | Knowledge and applied understanding of the target role. | Knowledge items and scenario tasks. |
| Practical | Quality of a real work simulation. | Work artifact scored against a rubric, plus reviewer check. |
| Communication | Written and voice client communication. | Situational responses and intro video transcript. |
| English | Functional workplace English. | Written, listening and speaking tasks. |
| AI Fluency | Effective, safe and verified AI-assisted workflow. | Scenario and practical exercise. |
| Portfolio Evidence | Strength and verifiability of prior work. | Source files, version history, client confirmation. |
| Reputation | Performance inside Taskopedia. | Reviews, completion, repeat work, disputes. |
| Reliability | Delivery behaviour, not personality inference. | On-time milestones, responsiveness, attendance where contracted. |
How a score is calculated
A dimension score is the weighted mean of the scored items within it. Confidence is calculated separately, as the product of how much of the blueprint the evidence actually covers, how reliable the assessment instrument is, and whether a human reviewed the result.
dimension_score = Σ(item_score × item_weight) / Σ(item_weight) confidence = evidence_coverage × assessment_reliability × review_factor published_score = round(dimension_score)
The weights are held in versioned configuration that is reviewed and published, never inside a prompt. A result is always pinned to the assessment version it was taken under, so changing a rubric never silently rewrites scores that already exist.
Confidence is deliberately kept separate from the score. A high score with low confidence means we do not yet have enough evidence, not that the person is weak. Where confidence falls below threshold, the result goes to a human reviewer instead of being published as a precise number.
Role weightings in use
Different roles weight the dimensions differently. These are starting configurations and are being validated against real job outcomes; they will change by version as we learn which signals actually predict performance.
brand designer
brand-designer-v1.0
- Practical35%
- Role competency20%
- Portfolio evidence15%
- Communication10%
- AI fluency10%
- Reputation/reliability10%
customer success
customer-success-v1.0
- Communication25%
- Role competency20%
- Practical scenario20%
- English15%
- Reputation/reliability10%
- Tools/AI fluency10%
full stack developer
full-stack-developer-v1.0
- Practical code35%
- Role competency25%
- Debugging/security15%
- Communication10%
- AI coding fluency10%
- Reputation5%
digital marketer
digital-marketer-v1.0-derived
- Practical campaign brief30%
- Channel fundamentals and analytics25%
- Copy judgement and reporting20%
- AI research and verification15%
- Reputation/reliability10%
virtual assistant
virtual-assistant-v1.0-derived
- Prioritisation scenario25%
- Organisation, scheduling and tools25%
- Written communication and client updates20%
- English10%
- AI productivity workflow10%
- Reputation/reliability10%
sales sdr
sales-sdr-v1.0-derived
- Outreach and pitch25%
- Prospecting, ICP reasoning and CRM25%
- Objection handling20%
- English10%
- Ethical AI-assisted research10%
- Reputation/reliability10%
ai engineer
ai-engineer-v1.0-derived
- Practical modelling task35%
- Model, data and evaluation knowledge25%
- Explaining a result15%
- Responsible AI workflow15%
- Reputation/reliability10%
data analyst
data-analyst-v1.0-derived
- Practical analysis30%
- SQL, statistics and reporting30%
- Turning analysis into a recommendation20%
- AI-assisted analysis10%
- Reputation/reliability10%
cybersecurity analyst
cybersecurity-analyst-v1.0-derived
- Threat, vulnerability and response knowledge35%
- Practical triage30%
- Incident reporting15%
- AI-assisted detection10%
- Reputation/reliability10%
devops engineer
devops-engineer-v1.0-derived
- Practical pipeline task35%
- Cloud, CI/CD and observability30%
- Runbooks and handover15%
- AI-assisted operations10%
- Reputation/reliability10%
qa engineer
qa-engineer-v1.0-derived
- Practical test suite30%
- Test design and tooling30%
- Defect reporting20%
- AI-assisted testing10%
- Reputation/reliability10%
ux designer
ux-designer-v1.0-derived
- Practical flow or screen30%
- Research, patterns and accessibility20%
- Portfolio evidence15%
- Design rationale15%
- AI-assisted design10%
- Reputation/reliability10%
video editor
video-editor-v1.0-derived
- Practical edit35%
- Editing, motion and delivery craft20%
- Portfolio evidence15%
- Responding to a brief10%
- AI-assisted production10%
- Reputation/reliability10%
content writer
content-writer-v1.0-derived
- Practical writing piece30%
- Brand voice and editing to feedback20%
- Research, structure and search intent20%
- English10%
- AI-assisted drafting and fact-checking10%
- Reputation/reliability10%
finance accountant
finance-accountant-v1.0-derived
- Bookkeeping, reconciliation and reporting35%
- Practical month-end task30%
- Explaining the numbers15%
- AI-assisted finance workflow10%
- Reputation/reliability10%
hr recruiter
hr-recruiter-v1.0-derived
- Sourcing, screening and people process30%
- Practical shortlist exercise25%
- Candidate and manager communication20%
- English5%
- AI-assisted sourcing10%
- Reputation/reliability10%
ecommerce specialist
ecommerce-specialist-v1.0-derived
- Storefront, merchandising and analytics30%
- Practical store task30%
- Customer and supplier messaging20%
- AI-assisted listing and support10%
- Reputation/reliability10%
legal support
legal-support-v1.0-derived
- Documents, research and confidentiality30%
- Practical drafting task25%
- Client correspondence15%
- English15%
- AI-assisted review5%
- Reputation/reliability10%
cad technician
cad-technician-v1.0-derived
- Practical drawing task35%
- Standards, tooling and take-off30%
- Mark-ups and revisions15%
- AI-assisted drafting10%
- Reputation/reliability10%
medical back office
medical-back-office-v1.0-derived
- Terminology, coding and records35%
- Practical claim or record task25%
- Patient and practice correspondence15%
- English10%
- AI-assisted administration5%
- Reputation/reliability10%
research analyst
research-analyst-v1.0-derived
- Practical research brief30%
- Design, sources and data collection25%
- Writing up findings20%
- AI-assisted research and verification15%
- Reputation/reliability10%
supply chain coordinator
supply-chain-coordinator-v1.0-derived
- Sourcing, planning and documentation35%
- Practical purchasing exercise25%
- Supplier negotiation and chasing20%
- AI-assisted planning10%
- Reputation/reliability10%
project manager
project-manager-v1.0-derived
- Practical plan or recovery exercise30%
- Planning, risk and delivery method25%
- Stakeholder updates25%
- AI-assisted coordination10%
- Reputation/reliability10%
automation specialist
automation-specialist-v1.0-derived
- Practical automation build35%
- Process mapping, tooling and integration30%
- Handover documentation15%
- AI inside a process, with checks10%
- Reputation/reliability10%
game developer
game-developer-v1.0-derived
- Practical prototype35%
- Engine, gameplay and performance30%
- Working with designers and artists15%
- AI-assisted tooling10%
- Reputation/reliability10%
embedded engineer
embedded-engineer-v1.0-derived
- Practical firmware task35%
- Firmware, interfaces and connectivity30%
- Technical documentation15%
- AI-assisted debugging10%
- Reputation/reliability10%
Where AI is used, and where it is not
AI assists with
Structuring an imported CV into a draft profile, which the talent must confirm.
Generating question variants from an approved competency blueprint.
Applying a written rubric to a text, voice or artifact response.
Transcribing audio and generating captions.
Turning an employer description into a structured role brief.
Phrasing a match explanation from features that already exist in the ranking data.
AI never
Decides the competency weights or the pass threshold at run time.
Publishes a score without schema validation and version metadata.
Issues a verification badge or removes access to opportunities on its own.
Adds a reason to a match explanation that is not present in the feature data.
Infers personality, honesty or emotion from a face or a voice.
Claims to determine whether a design or document was AI-generated.
Every evaluator run records the provider, model, prompt template version, rubric version and a confidence value, so any published score can be reconstructed and audited later.
Verification states
| State | Meaning | What employers see |
|---|---|---|
| Profile created | Self-declared information, not yet checked. | No badge. |
| Identity verified | Identity check passed. | Identity badge only. |
| Assessment completed | Required assessments done, quality review may still be pending. | Scores provisional and visible to the talent only. |
| Taskopedia Verified | Role thresholds met, required checks passed, human QA complete. | Verified badge with date and assessment version. |
| Verified, active evidence | Recent assessment or work evidence on file. | Full badge. |
| Verification stale | Evidence has aged beyond the freshness window. | Badge annotated as reassessment due, or downgraded by policy. |
| Under review | A material flag or appeal is open. | Affected scores limited until resolved. This does not imply wrongdoing. |
Common questions
- Does AI decide whether I pass an assessment?
- No. AI applies a written rubric to produce a per-item score, but the weights, the pass thresholds and the aggregation are held in versioned configuration and computed in code. Low-confidence and borderline results are routed to a human reviewer before anything is published, and no badge is issued without human quality review.
- What does the confidence value next to a score mean?
- Confidence is calculated separately from the score, as the product of how much of the assessment blueprint the evidence actually covers, how reliable the instrument is, and whether a human reviewed the result. A high score with low confidence means we do not yet have enough evidence, not that the person performed poorly.
- Can I challenge a result I think is wrong?
- Yes. Any score that materially affects your verification status or your access to opportunities can be appealed. An appeal creates a tracked case with a named reviewer who was not involved in the original decision. If a score is overridden, the original result is preserved alongside the new one with the rationale and policy basis recorded.
- Do you assess personality, confidence or honesty from my video?
- No. We do not use facial expression, emotion inference, honesty detection, attractiveness scoring or accent ranking. Communication is scored on observable criteria such as clarity, structure, professionalism, completeness and expectation setting, using the transcript and a written rubric.
- Can I use AI in a practical assessment task?
- Yes, and we assess how well you do it. AI fluency is a scored dimension covering whether you use AI effectively, verify its output and understand its limitations. What matters is that you disclose how AI was involved and that the resulting work is good. We do not claim to detect AI-generated work from the artifact alone.
- Will my scores change if you update a rubric?
- No. Every result is pinned to the assessment version it was taken under, and published assessment versions are immutable. Changing a rubric affects future sessions only. If you want a result under a newer version, you take a reassessment.
- How long does verification stay valid?
- Each role track has a freshness window. Once your most recent assessment or completed work falls outside it, your profile is marked as due for reassessment rather than presented to employers as current evidence.
Integrity and appeals
Assessments use randomised item pools, server-side timing and per-section limits. Where integrity signals are recorded, they are disclosed in advance, and they never automatically fail anyone. A flag routes a session to a human reviewer who looks at the actual evidence.
We do not use invasive webcam proctoring by default. Any future use would require a clear justification, explicit consent and legal review first.
Any score that affects verification or access to opportunities can be appealed. An appeal creates a tracked case with a named reviewer. If a score is overridden, the original result is preserved alongside the new one with the reviewer, rationale and policy basis recorded.