Slide Welcome to Vancouver’s Immigration Blog Practicing exclusively in the field of Canadian Immigration Law, I started Vancouver Immigration Law Blog to provide community resources and community support to those navigating Canada’s complicated immigration system. I am the Principal/Owner of Heron Law Offices, a boutique immigration and refugee law firm based in Vancouver and Burnaby, British Columbia. LEARN MORE Slide Visit My Firm Website - Heron Law Offices LEARN MORE Slide Follow Our Advocacy, Research, and Education Activities at Arenous Foundation LEARN MORE

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[Legal Rant] Addressing “Gaming the System” Concerns – Indian Study Permit Applicants and the SDS Example

 

Perhaps this post is inevitable. The reach of s.91 IRPA might be difficult to both control or manage from here inside Canada. Other than bulk refusing the applicants of certain unauthorized practitioners/agents that are found (and it appears only in egregious cases), it is highly unlikely we will see any enforcement. We will try and cut off the Canadian links, but too often they go under the surface – a quick Use of Rep signed here, a quick portal creation there, and the situation goes unnoticed by the applicant and our system-defending officers.

What is increasingly troublesome, however, is that there appear to be ways the system is being effectively gamed – or at least it is being marketed this way. As part of my work I am quite public on Twitter and Social media, and invite those with tips and leads to tell what is going on – ground level. This is one of those tips I received.

Here is one case that I think should trouble some folks.

Canada’s Student Direct Stream (SDS) has been lauded by many in the policy space for creating a subcategory of ‘ready-to-study’ students with good language scores, funds to pay for first year tuition, and a GIC. While I do not have recent stats and need to obtain them, the benefits of these programs have historically been faster processing and higher (10-12%) approval rates to reward students who did the leg work. One of the unique features of the SDS Application is that the approval (and refusal) is issued at Case Processing Centre (“CPC”) Edmonton in Canada, taking a large weight off the local visa offices and triaging cases more effectively.

I also want to give a bit of a context for writing this piece. A study permit was refused and the individual decided to go to an unauthorized representative for the subsequent follow-up application. That agent told the individual that previous counsel had provided too many explanations and letters and that the key to approval was to ensure the Visa Application Centre (“VAC”), and by extension the local visa office, could flag the file after submission. They recommended against submitting another SDS application.

Based on my credible source, who has canvassed other immigration agents from India, who confirmed same – the on the ground knowledge now is that SDS Applications will now take significant longer than regular applications and that to get approvals, the best thing to do is to get the office processed at the local level, at Delhi.

The way to do this is two fold:

  1. Make sure the language test done is the PTE – so that the file has to be processed locally in Delhi; and
  2. Make sure that only first semester and not first year tuition is paid to avoid SDS processing and keep the file local.

This is not the first time we have heard of a perceived preferential processing for non-SDS applications. Similarly for applicants from Philippines and Pakistan we have heard similar things in the past – along with Applicants that have taken various tips to try and get their cases triaged differently. These seem to be amplified concern of Applicants by the fact September school deadlines are starting and applicants need quicker decisions rendered than the SDS ones that have been taking several months. Agents are telling students (and apparently results are showing) approvals at the local office level.

RANT: I think we have to get to a point now, where we ask ourselves why we would create a stream like SDS only to have it take longer to process and perhaps offer less competitive processing.

Without the stats at this stage, I can only pass over the anecdotes I am hearing, but there is enough of a concern on the ground (I am not going to use the word qualitative this week – it doesn’t work) that applicants are being guided by unauthorized practitioners into ‘gaming the system.’ I believe it is enough of a concern that someone should step in to ensure transparency and proper communication.

Either there should be no discrepancy in processing times (thus removing the incentive of speed) or there should be a clear policy aim to have significantly higher approval rates for SDS than non-SDS streams, as should be the case on the basis of the required documentation to be submitted and obtained prior to application.

As IRCC moves to implement technological changes and institute these rules that will triage applications, it must be very aware of those who may have unauthorized access to or are learning how these rules work so as to want to circumvent them. If the data also comes out (beyond anecdotal) to support certain actions, applicants will adjust their behaviours and will be led to do so by unauthorized reps.

If SDS is the superstar program, worthy of global expansion, it is marketed as – there’s no reason it should take longer and make one’s applicant less likely to succeed. The doors of exploitation open up if there’s not consistency in this.

[End of Rant]

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Ocran v. Thavaratnam and Hoku: How a Chinook Decision is Bootstrapped in Judicial Review and Strategies to Counter

I am writing this post after noticing a troubling trend and pattern. Unfortunately, counsel who are unprepared for how the Department of Justice and IRCC work in tandem on these cases (and to be honest, some Judges have also fallen into the trap of this strategy) can lead to JRs being dismissed at leave.

Here’s the pattern:

  1. Temporary Resident Refusal – template refusal letter, further templated GCMS notes – these refusals are done on template refusal language. The refusal letter contains template grounds, and then the GCMS notes indicates further broad refusal grounds using such grounds as concerns about the applicant being ‘young, single, and mobile’, concerns about the ‘applicant’s family ties in Canada,’ the studies not being a ‘reasonable expense’, or the applicant’s ‘past mark sheets’ being of concern – among many others.
  2. Judicial Review – Applicant’s Record – Filed By Applicant – Usually on grounds that only conclusion statements are made, limited reference to material facts, speculative – therefore not intelligible, transparent or justifiable (Vavilov);
  3. Respondent’s Memorandum – Applicant is trying to relitigate facts – onus is on Applicant to prove they meet requirements, Officer’s not required to consider every fact, decision is reasonable. The DOJ then goes out of their way to usually add some detail or justification (I call this portion bootstrapping or counsel’s speculation) to tie together the pieces of the decision.
  4. Judge renders leave decision (refused) or grants hearing  but renders decision that may actually be seeking to question the Applicant’s efforts to provide evidence or question why not more was not provided – Judge often times stepping into the role of bootstrapping or speculating). Counsel tries to argue back that strong evidence was provided, and case becomes about relitigating and justification based on evidence before decision-maker (Applicant loses, often).

 

Assertions of Facts/Consideration of Evidence Leading to Conclusion or Just Conclusions With No Facts

If I wanted to refuse a study permit application reasonably, I could reasonably do it. Highlight some sort of shortcoming/mis-step/inadequacy of evidence, tie it somehow to a refusal ground, and lead to a conclusion that the Officer was not convinced.

However in this new Chinook world, the conclusions often come first and in fact (unintentional), there are little to no actual facts in decisions. This is because, as we know, decisions are being bulk refused and in other times Officers do not have enough time to properly suss out the facts short of stopping at the first grey area they see.

Very commonly decisions read like this:

The Applicant has a girlfriend in Canada. Therefore the applicant’s family ties and economic ties do not satisfy me they will leave Canada at the end of their authorized stay.

Unfortunately there is no logical leap step between Fact or Finding, or even if there is, there’s some obligation to consider evidence that might lead to an opposite finding, which rarely happens.

 

Reverse Engineering Decision – DOJ’s Position Supported by Ocran v. Canada (Citizenship of Immigration) 2022 FC 175 

I generally love his decisions – and his interpretation and application of Vavilov is top notch, but I would say Justice Little’s decision in Ocran is one where it went beyond a judicial review of the decision (para 24 onwards) to almost a stepping in the shoes of the Officer to re-evaluate the factual record in light of the sparse GCMS notes. In no part of the decision, does Justice Little actually address the flawed nature of analysis based on a ‘reading in’ of justifying evidence. In short, I think Ocran opens up (and maybe I read Vavilov the wrong way) to reverse engineering a refusal decision based on stated conclusions with limited factual reliance by the decision-maker.

The approach taken in Ocran has inspired the same process by Department of Justice in cases, and unsurprisingly the decision is being cited for that preposition now that the Record can be read into the sparse GCMS notes. The harm of this is that template language that never meant to analyze or apply the facts to a reached decision are now retroactively used to justify that decision-made.

While I celebrated (sort of) the decision of Justice Little not to break down/opine on the Chinook system, perhaps having sought to contextualize how Officers render their decision template decision using Chinook would have kept him from stepping in to provide as detailed of a factual analysis as he did.

As a side note, even more worrisome is that I have seen after judicial review (consent), a case go back to IRCC where the Officer refused again and did so by adding one line of fact (citing the Record) between each of their previously templated decisions. In short, it is not difficult to rewrite a Chinook decision to make it reasonable even if it was found unreasonable at first.

 

How to Counter – Thavaratnam v. Canada (MCI) 2022 FC 967 

On the more hopeful side of things, a recent decision by Madam Justice Furlanetto in Thavartnam gives applicant’s more hope.

In this decision, the Officer refused a temporary resident visa for an applicant from Sri Lanka, utilizing what Madam Justice Furlanetto refers to in para 19 as blanket or boilerplate statements and a series of conclusions (para 20).

She notes the gaps in reasoning from the Officer and the attempts of the DOJ to try and explain them, but concludes that this does not cure in inadequacy of the reasons for decision.

She writes:

[24] The Respondent proposes various explanations for the Officer’s conclusions. It asserts that the Applicant’s ties to Sri Lanka are weak when weighed against his family residing in Canada because only his wife is in Sri Lanka and they have no children. The Respondent asserts that the Applicant’s savings equate to $18,000 CAD and his pay for the year $5,000 CAD, which is extremely low by Canadian standards. It suggests that the business activities cannot be verified because they are training activities at a private organization owned by a relative. These explanations, however, were not those given in the GCMS notes. Counsel’s speculation of a plausible explanation cannot cure the inadequacy of the reasons for decision (Asong Alem v Canada (Citizenship and Immigration), 2010 FC 148 [Asong Alem] at para 19).

This is a paragraph that needs to be commonplace in responses where the DOJ seeks to try and take the reasons beyond what is written to piece together, what are gaps on the page. (Recall: Komolafe v Canada (Minister of Citizenship and Immigration), 2013 FC 431, 16 Imm. L.R. (4th) 267, at para 11.)

 

Contexualizing Bootstrapping for the Federal Court – Hoku v. Canada (Citizenship and Immigration), 2019 FC 362

I often start my contexualizing my reply’s with the DOJ’s practice. Again, Ilike to use the language of bootstrapping borrowing from wording of Justice Ahmed.

Respondent’s Position re: Family Ties Bootstraps the Officer’s Decision and Commits the Same Error as the Officer of Failing to Analyze Family Ties

3. With respect, the Respondent’s submissions regarding family ties bootstraps the decision of the Officer in this matter. Justice Ahmed writes in Hoku v. Canada (Citizenship and Immigration), 2019 FC 362 [“Hoku”] at para 13 about the practice of bootstrapping.

[13] The Applicant also submits that her detailed submissions and supporting documents were not considered. The Applicant explains that this evidence included her immigration history, personal background, bona fides about her spiritual healing, the nature of her criminal conviction, and indicia of rehabilitation. The Applicant points out that the Minister’s Policy Manual states that all of these factors must be considered, and argued that the Respondent’s submissions bootstrap the actual decision and the reasons discernable from the GCMS notes.

[14] The Respondent submits that the Applicant simply failed to establish that her circumstances justify issuing an ARC, which is not intended to routinely allow persons to overcome a deportation order (Andujo at para 26). The Respondent also submits that it is unclear if the Applicant explained to the Decision-Maker that she exited Canada to comply with her probation order and objects to any inclusion of information not before the Decision-Maker.

[15] First, I agree with the Applicant that the Respondent’s submissions bootstrap the actual Decision-Maker’s reasoning. For example, there is nothing to support the Respondent’s Memorandum at paragraph 16 which states that the Decision-Maker found that the Applicant’s reasons for requesting an ARC were not compelling.
(emphasis added)

Hoku at para 13.

I often then apply and highlight what the DOJ says and respond as follows:

The reality is that the Officer does not offer any justification for the templated reasons they have provided. The Officer merely states that the Applicant “is single, mobile, is not well established and has no dependents.” The Respondent is attempting to fill in the gaps on the page with their own analysis, which is not the purpose of judicial review and represents the very process of bootstrapping.

I hope this piece was helpful. Again, I love the judicial review practice and am excited to make an announcement in September (so soon!) about our further shift towards this direction and this work. I hope young counsel interested in the work slow down and do their research, before engaging DOJ on a Chinook refusal JR.

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The High Refusal Rate for C42 Spousal Applicants at the Abu Dhabi VO: A Closer Look

I recently received some very interesting data from IRCC for a conference I am presenting at in October.

While I will be assembling a team to break down this data (with the help of a trained data scientist), I wanted to write a short piece following a long blog hiatus on probably the data statistic that on the face stands out the most from my first glance.

This stat is the high refusal rate of C42 (spouse of FT study permit holder) applicants who apply at the Abu Dhabi Visa Office in the UAE.

I have extracted the data below.

 

he benefit of doing both Country of Citizenship and Country of Residence disaggregations is it not only shows the major discrepancies on the face (that only 17%/18% of Abu Dhabi VO applicants are getting approved versus 64%/62% as a global rate* – excluding in Canada + Extension apps) but also to see who makes up the large majority of applicants and where do they live. While in my practice I have been quite attuned to the challenges of Indian and Pakistan applicants living in the UAE, I am definitely surprised by the number of Philippines applicants being decided in Abu Dhabi UAE.

The broader implications of this of course means that either initial applications are being refused alongside but possibly that also several families are being separated with a Principal Applicant being approved and the spouse refused. These cases have appeared on my desk quite often recently.

If I were to chalk the C42 refusals to a central reason (and again, even our refusal grounds data – isn’t disaggregated properly right now), I think the lack of citizenship and instability of residency in the UAE is a contributing factor. Many residency permits are tied to work or study in UAE by the Principal Applicant, and there are many non-Emirates in the UAE who go whole lives and generations without ever getting full citizenship. Another factor could be also the deciding of cases of non-citizens of a country at that country’s visa office. We’re increasingly learning of triaging that involves visa offices in Europe handling backlogs from Asia/Africa, and this may be a very similar case particularly for the study permits from the Philippines.

This data set was not easy to get. I had to push to get the data disaggregated and after it was received it had several mistakes. It took two months of back and forths just to get to this point.

This is probably just 0.01% of the work will need to be done. Again, I am not even a data analyst which is why I have put out the call to others in the field and am really impressed by all the responses of offers to help.

I look forward to presenting this data in October. Thanks for tuning in (as always)!

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Coach Will: New Vocabulary Words Tomorrow’s Immigration Practitioners Will Need To Know

As a resource, and to buy time as I am writing more substantive blogs, I wanted to share a #CoachWill blog on new vocabulary, terminology that tomorrow’s immigration practitioners will need to know, learn, advise their clients on, and spend time with. I am still very much learning these terms and their impact, but it gives us a mutual starting point to grow our knowledge of how Canadian immigration law will be impacted moving forward:

 

Advanced Analytics: which is composed of both Predictive and Prescriptive components, consists of using computer technology to analyze past behaviours, with the goal of discovering patterns that enable predictions of future behaviours. With the aid of a team of computer science, data, IT, and program specialists, AA may result in the creation of a model that can perform risk triage and enable automated approvals on a portion of cases, thereby achieving significant productivity gains and reducing processing times. [As defined in IRCC’s China-Advanced Analytics TRV Privacy Impact Assessment]

Artificial Intelligence: Encompassing a broad range of technologies and approaches, Al is essentially the field of computer science dedicated to solving cognitive problems commonly associated with human intelligence, such as learning, problem solving, and pattern recognition. [As defined in IRCC’s Policy Playbook on Automation]

 

Automated decision support system: Includes any information technology designed to directly support a human decision-maker on an administrative decision (for example, by providing a recommendation), and/or designed to make an administrative decision in lieu of a human decision-maker. This includes systems like eTA or Visitor Record and Study Permit Extension automation in GCMS. [As defined in IRCC’s Policy Playbook on Automation]

 

Black Box: Opaque software tools working outside the scope of meaningful scrutiny and accountability. Usually deep learning systems. Their behaviour can be difficult to interpret and explain, raising concerns over explainability, transparency, and human control. [As defined in IRCC’s Policy Playbook on Automation]

 

Deep learning/neural network is a subset of machine learning, which is essentially a neural network with three or more layers. These neural networks attempt to simulate the behavior of the human brain—albeit far from matching its ability—allowing it to “learn” from large amounts of data. While a neural network with a single layer can still make approximate predictions, additional hidden layers can help to optimize and refine for accuracy. [As defined by IBM: https://www.ibm.com/cloud/learn/deep-learning#:~:text=Deep%20learning%20is%20a%20subset,from%20large%20amounts%20of%20data] 

 

Exploration zone: The exploration zone – also referred to as a “sandbox” – is the environment used for
research, experimentation and testing related to advanced analytics and Al. Data, codes and software
are isolated from those in production so that they can be tested securely.
“Fettering” of a decision-maker’s discretion: Fettering occurs when a decision-maker does not
genuinely exercise independent judgment in a matter. This can occur when a decision-maker binds
him/herself to a fixed rule of policy, another person’s opinion, or the outputs of a decision support
system. Although an administrative decision-maker may properly be influenced by policy considerations
and other factors, he or she must put his or her mind to the specific circumstances of the case and not
focus blindly on one input (e.g. a risk score provided by an algorithmic system) to the exclusion of other
relevant factors. [As defined in IRCC’s Policy Playbook on Automation]

 

“Fettering” of a decision-maker’s discretion: Fettering occurs when a decision-maker does not
genuinely exercise independent judgment in a matter. This can occur when a decision-maker binds
him/herself to a fixed rule of policy, another person’s opinion, or the outputs of a decision support
system. Although an administrative decision-maker may properly be influenced by policy considerations
and other factors, he or she must put his or her mind to the specific circumstances of the case and not
focus blindly on one input (e.g. a risk score provided by an algorithmic system) to the exclusion of other
relevant factors. [As defined in IRCC’s Policy Playbook on Automation]

 

Machine learning: A sub-category of artificial intelligence, machine learning refers to algorithms and statistical models that learn and improve from examples, data, and experience, rather than following pre-programmed rules. Machine learning systems effectively perform a specific task without using explicit instructions, relying on models and inference instead. [As defined in IRCC’s Policy Playbook on Automation]

 

A minimum viable product (MVP) is a development technique in which a new product or website is developed with sufficient features to satisfy early adopters. The final, complete set of features is only designed and developed after considering feedback from the product’s initial users. [As defined by Techopedia – https://www.techopedia.com/definition/27809/minimum-viable-product-mvp] 

 

Predictive Analytics: brings together advanced analytics capabilities spanning ad-hoc statistical analysis, predictive modeling, data mining, text analysis, optimization, real-time scoring and machine learning. These tools help organizations discover patterns in data and go beyond knowing what has happened to anticipating what is likely to happen next. [As defined in IRCC’s China-Advanced Analytics TRV Privacy Impact Assessment]

 

Prescriptive Analytics: Prescriptive Analytics is an advanced analytics technology that can provide recommendations to decision-makers and help them achieve business goals by solving complicated optimization problems. [As defined in IRCC’s China-Advanced Analytics TRV Privacy Impact Assessment]

 

Process automation: Also called “business automation” (and sometimes even “digital transformation”), process automation is the use of digital technology to perform routine business processes in a workflow. Process automation can streamline a business for simplicity and improve productivity by taking mundane repetitive tasks from humans and giving them to machines that can do them faster. A wide variety of activities can be automated, or more often, partially automated, with human intervention maintained at strategic points within workflows. In the domain of administrative decision-making at IRCC, “process automation” is used in contrast with “automated decision support,” the former referring to straightforward administrative tasks and the latter reserved for activities involving some degree of judgment. [As defined in IRCC’s Policy Playbook on Automation]

[Last Updated: 19 April 2022 – we will continue to update as new terms get updated]

 

 

 

 

 

 

 

 

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My Value Proposition

My Canadian immigration/refugee legal practice is based on trust, honesty, hard-work, and communication. I don’t work for you. I work with you.

You know your story best, I help frame it and deal with the deeper workings of the system that you may not understand. I hope to educate you as we work together and empower you.

I aim for that moment in every matter, big or small, when a client tells me that I have become like family to them. This is why I do what I do.

I am a social justice advocate and a BIPOC. I stand with brothers and sisters in the LGBTQ2+ and Indigenous communities. I don’t discriminate based on the income-level of my clients – and open my doors to all. I understand the positions of relative privilege I come from and wish to never impose them on you. At the same time, I also come from vulnerability and can relate to your vulnerable experiences.

I am a fierce proponent of diversity and equality. I want to challenge the racist/prejudiced institutions that still underlie our Canadian democracy and still simmer in deep-ceded mistrusts between cultural communities. I want to shatter those barriers for the next generation – our kids.

I come from humble roots, the product of immigrant parents with an immigrant spouse. I know that my birth in this country does not entitle me to anything here. I am a settler on First Nations land. Reconciliation is not something we can stick on our chests but something we need to open our hearts to. It involves acknowledging wrongdoing for the past but an optimistic hope for the future.

I love my job! I get to help people for a living through some of their most difficult and life-altering times. I am grateful for my work and for my every client.

Awards & Recognition

Canadian Bar Association Founders' Award 2020

Best Canadian Law Blog and Commentary 2019

Best New Canadian Law Blog 2015

Best Lawyers Listed 2019-2021

Best Canadian Law Blog and Commentary 2021

Canadian Bar Association Founders' Award 2020

Best Canadian Law Blog and Commentary 2019

Best New Canadian Law Blog 2015

Best Lawyers Listed 2019-2021